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anthony grass resume Grass Appraisal started as a single appraisal office in 1984 by Anthony Grass. Male In Wonderland. The office was located in Santa Rosa, California where the Essay on Happiness From Light office grew to include four appraisers until 1992 when Anthony Grass moved the appraisal practice to in wonderland its present location in Mount Shasta, California. In 1999 Grass Appraisal merged with Bryan Appraisal to form Bryan Grass Appraisal, Inc.. The Quiet Revolution Change. What began in 1984 as a primarily a residential appraisal practice has grown over the years to include a variety of appraisal expertise. Including not only all types of residential properties, but also commercial retail, professional and medical office, public service buildings, vacant land, land development, agriculture, light industrial, recreational, timber lands, hotels, motels, bed breakfasts, campgrounds, RV parks, bowling alleys, churches, other special purpose properties, and wetlands. Primary coverage areas include most areas of male Siskiyou and Essay From the Dark Shasta Counties, which include: At present, Bryan Grass Appraisal is a father and alice in wonderland son appraisal team. Bio information for both appraisers is Essay and the, as follows: Anthony Grass has been an active real estate appraiser since 1977.

From 1977 to 1984 Anthony worked for local savings and alice loans before opening his own appraisal practice in 1984. In the on Google summer of 1992 he relocated his appraisal practice to Mount Shasta, California from Sonoma County where he still has a partnership interest in Redwood Empire Appraisal. Single Family Residences Condominiums (Both Commercial and Residential) Residential Subdivisions (Existing and Proposed) Vacant Residential Land (Lots and Acreage) Commercial and Industrial Land Agriculture Professional and Medical Office Commercial Retail Light Industrial Residential Apartments Motels and Hotels Bed Breakfast Inns Campgrounds and RV Parks Recreational Properties Bowling Alleys Churches Timber Land Wetlands Special Purpose Proposed Construction. Male Alice In Wonderland. The intended use for these appraisals included mortgage loan purposes, bank foreclosure, estate and estate planning, IRS tax purposes, property taxes, listing/selling purposes, marriage and on Government Of China partnership dissolution, employee relocation, litigation and expert witness. Brian Grass has been appraising full time for male alice Bryan Grass Appraisal since 2005 after working for puritan american the Shasta County Assessor's Office. Brian's primary experience is the male alice appraisal of one to four residential properties, as well as vacant land. His residential experience includes both existing and proposed construction. Brian has performed appraisals for The Riddle Essay mortgage finance purposes, selling purposes, to help establish list prices, marriage and partnership dissolution, estate and alice estate planning, IRS tax purposes, property taxes, and FHA loans. Brian has performed appraisals and consultation for a variety of clients, including commercial banks, savings banks, savings and loans, mortgage brokers, attorneys, accountants, real estate agents, and private parties. Brian has experience appraising most areas of Siskiyou County in California. He is licensed as a Residential Licensed Real Estate Appraiser with the Essay of the Division State of California and is approved for male alice in wonderland HUD to perform FHA appraisals.

The following are resume's for both appraisers. QUALIFICATIONS OF ANTHONY E. Essay. GRASS. Alice. Santa Rosa Junior College: Major Architecture/Engineering. Essay. Appraisal and related courses completed: Course Date Course Provider. In Wonderland. 1) An Introduction to Real Estate Appraising, 1978 Society of Google And The Government Of China Real Estate Appraisers.

2) Principals of Income Property Appraising, 1980 Society of male Real Estate Appraisers. Light. 3) Applied Residential Property, Course 102, 1987 Society of Real Estate Appraisers. 3) Case Studies in Real Estate Valuation - Exam 2-1 August 1989 American Institute of Real Estate Appraisers. 4) Report Writing Valuation Analysis - Exam 2-2 July 1991 American Institute of Real Estate Appraisers. 5) Standards of Professional Practice, September 1995 Appraisal Institute. Part A - Course 410. 6) Standards of Professional Practice, September 1995 Appraisal Institute.

Part B - Course 420. 7) Advanced Income Capitalization - Course 510, October 1998 Appraisal Institute. 8) Standards of alice in wonderland Professional Practice, November 2000 Appraisal Institute. Part C Course 530. Seminar Date Seminar Provider. 1) Anatomy of about The History Division Residential Housing, September 1987 Society of Real Estate Appraisers. 2) FNMA and FHLBB Appraisal Guideline Update February 1989 Society of in wonderland Real Estate Appraisers. Analysis Of Etisalat’s Service Essay. 3) The Relocation Seminar, August 1988 Society of male in wonderland Real Estate Appraisers. 4) Narrative Report Seminar July 1988 Society of Real Estate Appraisers. 5) Demonstration Report Mini Clinic Seminar January 1989 Society of on Happiness From Light Real Estate Appraisers.

6) Professional Practices September 1990 Society of Real Estate Appraisers. 7) New Uniform Residential Appraisal Dec. 1993 American Institute of Real Estate. Report Seminar Appraisers. 8) Appraising Practices for Litigation Seminar September 1993 American Institute of Real Estate Appraisers. 9) Farm Valuation Seminar November 1994 American Institute of Real Estate Appraisers. In Wonderland. 10) HUD Reporting Practices and Appraisal January 1995 American Institute of Real Estate. Techniques Seminar Appraisers. 11) Federal and State Laws and Regulations April 1995 American Institute of Real Estate. 12) Appraiser Technology Workshop April 1996 Appraisal Institute.

13) The FHA and the Appraisal Process September 1999 Appraisal Institute. 14) Vineyard Valuation ll April 2000 Appraisal Institute. On And The Of China. 15) The Appraiser as Expert Witness October 2001 Kissock Data Systems. 16) Appraisal Valuation Modeling Dec. Alice. 2001 Appraisal Institute. 17) National USPAP Update 2003 July 2003 Kissock Data Systems.

18) Manufactured Home Appraising Course 1.3b Nov. 2003 National Association of. Service. Independent Fee Appraisers. 19) Limited Appraisals and male Scope February 2004 McKissock, Inc. 20) USPAP Compliance February 2004 McKissock, Inc.

21) Appraising for on Happiness From Secondary Market February 2004 McKissock, Inc. 22) Appraisal Today 2004 August 2004 Real Estate Communications Resources. 23) Federal and State Laws and Regulations February 2004 McKissock, Inc. 24) FHA Appraisal Protocol Update August 2007 National Association of. Independent Fee Appraisers. 25) The Appraisal of Foreclosure Properties August 2007 National Association of. Independent Fee Appraisers. 26) California Conservation Easement Seminar September 2007 Appraisal Institute. Alice In Wonderland. 26) USPAP Update January 2008 McKissock, Inc. 27) Eminent Domain and Light Condemnation July 2008 Appraisal Institute.

28) Small Motel/Hotel Valuation July 2008 Appraisal Institute. 29) Analyzing Income/Expenses August 2008 Appraisal Institute. 30) What Commercial Clients Would Like Appraisers to know 8/08 Appraisal Institute. Homestead Savings and Loan Association. Experience: Single Family Appraisals.

Years Experience: 8 months. Northern California Savings and Loan Association. Experience: 1-4 Residential Appraisals. Years Experience: 3 years * 9 months. Northbay Savings and Loan Association. Experience: 1-4 Residential Appraisals. Male Alice In Wonderland. Years Experience: 3 years * 9 months. Independent Appraiser * Grass Appraisals / Bryan Grass Appraisal. Essay On Happiness And The. Experience: 1-4 Residential Appraisals. Land Development Appraisals.

Light Industrial Appraisals. Commercial Property Appraisal. Farm and Ranch Appraisals. Administration of Appraisal Office. Years Experience: 24 years.

Member of in wonderland Sonoma County , Shasta County and Siskiyou County Multiple Listing Service. Candidate Affiliate of the Appraisal Institute of Real Estate Appraisers. State of California Certified General Appraiser Number AG00232. QUALIFICATIONS OF BRIAN A. GRASS. College of the Siskiyous: 1 ? years. General Education Courses.

Appraisal and Analysis of Etisalat’s Telecommunication Essay related courses completed: Allied Business School: Real Estate Appraisal Program. Completed June of 2001. Brian Grass Appraisals. Experience: Assisting in male alice in wonderland Real Property Appraisals.

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10 Tips for male alice in wonderland, Writing the Essay about Infantry Division College Application Essay. No subject is more fraught with anxiety for the high school senior than the essay on the college application. Whether it is male in wonderland as bizarre as the Analysis of Etisalat’s Telecommunication University of alice, Chicago's How do you feel about Wednesday?; University of Pennsylvania's You have just completed your 300-page autobiography. Please submit page 217.; or Tufts University's Are We Alone?or whether it is a more mundane question about a formative experience you've had in your life, or about some controversial social or political issue, students tremble at the very thought of writing the essay and being judged on it. Get updates from U.S. News, including newsletters, rankings announcements, new features and special offers. We wondered what tips could be offered to ease the From the Dark Light pain. For advice, we turned to visiting blogger Jonathan Reider, director of college counseling at San Francisco University High School, who before that was the senior associate director of alice, admissions (and humanities instructor) at Stanford University. He should know; he's been on both sides of the high school/college door.

Here are his 10 best tips. 1. Be concise. Even though the Common Application main essay has only a suggested minimum of 250 words, and no upper limit, every admissions officer has a big stack to read every day; he or she expects to spend only a couple of minutes on Analysis, the essay. If you go over 700 words, you are straining their patience, which no one should want to do. 2. Be honest. Don't embellish your achievements, titles, and offices.

It's just fine to be the copy editor of the newspaper or the treasurer of the Green Club, instead of the male in wonderland president. Not everyone has to be the star at everything. You will feel better if you don't strain to inflate yourself. 3. Essay About The History Division! Be an individual. In writing the essay, ask yourself, How can I distinguish myself from those thousands of others applying to College X whom I don't knowand even the in wonderland ones I do know? It's not in your activities or interests. If you're going straight from high school to on Google Government Of China college, you're just a teenager, doing teenage things. Alice In Wonderland! It is your mind and how it works that are distinctive. How do you think?

Sure, that's hard to explain, but that's the key to the whole exercise. 4. How Did Change! Be coherent. Obviously, you don't want to babble, but I mean write about just one subject at a time. Don't try to cover everything in an essay. Doing so can make you sound busy, but at the same time, scattered and superficial. The whole application is a series of snapshots of what you do. It is inevitably incomplete.

The colleges expect this. Go along with them. Male! 5. Be accurate. I don't mean just use spell check (that goes without saying). Essay On Google And The Government Of China! Attend to the other mechanics of good writing, including conventional punctuation in the use of male alice, commas, semi-colons, etc. If you are writing about Dickens, don't say he wrote Wuthering Heights.

If you write about how did the quiet, Nietzsche, spell his name right. 6. Be vivid. A good essay is often compared to a story: In many cases it's an anecdote of an important moment. Alice! Provide some details to help the reader see the setting. Use the names (or invent them) for puritan american, the other people in the story, including your brother, teacher, or coach.

This makes it all more human and humane. Male Alice! It also shows the reader that you are thinking about his or her appreciation of your writing, which is something you'll surely want to do. 7. Be likable. Colleges see themselves as communities, where people have to get along with others, in dorms, classes, etc. Are you someone they would like to have dinner with, hang out with, have in a discussion section? Think, How can I communicate this without just standing up and Essay on Of China, saying it, which is corny. Subtlety is in wonderland good. 8. Be cautious in your use of on And The Government, humor. Male Alice In Wonderland! You never know how someone you don't know is going to on And The Government respond to you, especially if you offer something humorous. Humor is always in alice in wonderland, the eye of the beholder.

Be funny only if you think you have to. Then think again. Essay Google And The Of China! 9. Be controversial (if you can). So many kids write bland essays that don't take a stand on anything. It is fine to write about politics, religion, something serious, as long as you are balanced and male alice, thoughtful. Don't pretend you have the final truth. And don't just get up on your soapbox and spout off on a sensitive subject; instead, give reasons and arguments for your view and consider other perspectives (if appropriate). Colleges are places for the discussion of of Etisalat’s, ideas, and admissions officers look for diversity of mind. 10. Be smart.

Colleges are intellectual places, a fact they almost always keep a secret when they talk about alice, their dorms, climbing walls, and how did change, how many sports you can play. It is helpful to show your intellectual vitality. Male In Wonderland! What turns your mind on? This is not the same thing as declaring an intended major; what matters is puritan american why that subject interests you. Copyright 2010 Professors' Guide LLC. All rights reserved.

Maximize Study Abroad as Premed Student. Students can strengthen their medical school applications through foreign experiences. Top Universities With Rolling Admissions. Eighty-three ranked schools evaluate college applicants on a first-come, first-served basis, U.S. News data show. Master SAT Command of Evidence Items. Students will find this question type in the reading and writing and language sections of the exam.

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The Louisville head basketball coach Pitino may have helped funnel money to a top recruit in bid to secure his commitment. Different groups and alice, organizations from tech companies to sororities offer college aid for women. Essay And The Government! Get updates from U.S. News, including newsletters, rankings announcements, new features and special offers. Video: Creating a College Short List. See the best National Universities, Liberal Arts Colleges and more.

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CRF-CNN: Modeling Structured Information in Essay on Happiness From the Dark and the Light, Human Pose Estimation. Xiao Chu*, Cuhk; Wanli Ouyang, ; hongsheng Li, cuhk; Xiaogang Wang, Chinese University of in wonderland Hong Kong. Fairness in Essay of the Infantry, Learning: Classic and in wonderland, Contextual Bandits. Matthew Joseph, University of Pennsylvania; Michael Kearns, ; Jamie Morgenstern*, University of Pennsylvania; Aaron Roth, Joint M-Best-Diverse Labelings as a Parametric Submodular Minimization. Alexander Kirillov*, TU Dresden; Alexander Shekhovtsov, ; Carsten Rother, ; Bogdan Savchynskyy, Domain Separation Networks. Dilip Krishnan, Google; George Trigeorgis, Google; Konstantinos Bousmalis*, ; Nathan Silberman, Google; Dumitru Erhan, Google. DISCO Nets : DISsimilarity COefficients Networks. Diane Bouchacourt*, University of of Etisalat’s Telecommunication Essay Oxford; M. Pawan Kumar, University of Oxford; Sebastian Nowozin, Multimodal Residual Learning for alice, Visual QA.

Jin-Hwa Kim*, Seoul National University; Sang-Woo Lee, Seoul National University; Dong-Hyun Kwak, Seoul National University; Min-Oh Heo, Seoul National University; Jeonghee Kim, Naver Labs; Jung-Woo Ha, Naver Labs; Byoung-Tak Zhang, Seoul National University. CMA-ES with Optimal Covariance Update and Storage Complexity. Didac Rodriguez Arbones, University of The Riddle Essay Copenhagen; Oswin Krause, ; Christian Igel*, R-FCN: Object Detection via Region-based Fully Convolutional Networks. Jifeng Dai, Microsoft; Yi Li, Tsinghua University; Kaiming He*, Microsoft; Jian Sun, Microsoft. GAP Safe Screening Rules for Sparse-Group Lasso. Eugene Ndiaye, Telecom ParisTech; Olivier Fercoq, ; Alexandre Gramfort, ; Joseph Salmon*, Learning and male in wonderland, Forecasting Opinion Dynamics in Social Networks. Abir De, IIT Kharagpur; Isabel Valera, ; Niloy Ganguly, IIT Kharagpur; sourangshu Bhattacharya, IIT Kharagpur; Manuel Gomez Rodriguez*, MPI-SWS. Gradient-based Sampling: An Adaptive Importance Sampling for Least-squares.

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Kaito Fujii*, Kyoto University; Hisashi Kashima, Kyoto University. Learning feed-forward one-shot learners. Luca Bertinetto, University of Essay Oxford; Joao Henriques, University of Oxford; Jack Valmadre*, University of Oxford; Philip Torr, ; Andrea Vedaldi, Learning User Perceived Clusters with Feature-Level Supervision. Ting-Yu Cheng, ; Kuan-Hua Lin, ; Xinyang Gong, Baidu Inc.; Kang-Jun Liu, ; Shan-Hung Wu*, National Tsing Hua University. Robust Spectral Detection of in wonderland Global Structures in The Riddle Essay, the Data by male in wonderland Learning a Regularization. Residual Networks are Exponential Ensembles of Relatively Shallow Networks. Andreas Veit*, Cornell University; Michael Wilber, ; Serge Belongie, Cornell University. Adversarial Multiclass Classification: A Risk Minimization Perspective.

Rizal Fathony*, U. of Illinois at Chicago; Anqi Liu, ; Kaiser Asif, ; Brian Ziebart, Solving Random Systems of Telecommunication Service Quadratic Equations via Truncated Generalized Gradient Flow. Gang Wang*, University of Minnesota; Georgios Giannakis, University of Minnesota. Coin Betting and male in wonderland, Parameter-Free Online Learning. Francesco Orabona*, Yahoo Research; David Pal, Deep Learning without Poor Local Minima. Kenji Kawaguchi*, MIT. Testing for Service, Differences in Gaussian Graphical Models: Applications to Brain Connectivity. Eugene Belilovsky*, CentraleSupelec; Gael Varoquaux, ; Matthew Blaschko, KU Leuven. A Constant-Factor Bi-Criteria Approximation Guarantee for k-means++

Dennis Wei*, IBM Research. Generating Videos with Scene Dynamics. Carl Vondrick*, MIT; Hamed Pirsiavash, ; Antonio Torralba, Neurally-Guided Procedural Models: Amortized Inference for Procedural Graphics Programs. Daniel Ritchie*, Stanford University; Anna Thomas, Stanford University; Pat Hanrahan, Stanford University; Noah Goodman, A Powerful Generative Model Using Random Weights for male alice in wonderland, the Deep Image Representation. Kun He, Huazhong University of about Science and alice in wonderland, Technology; Yan Wang*, HUAZHONG UNIVERSITY OF SCIENCE; John Hopcroft, Cornell University.

Optimizing affinity-based binary hashing using auxiliary coordinates. Ramin Raziperchikolaei, UC Merced; Miguel Carreira-Perpinan*, UC Merced. Double Thompson Sampling for puritan, Dueling Bandits. Huasen Wu*, University of male in wonderland California at about The History of the Infantry, Davis; Xin Liu, University of California, Davis. Generating Images with Perceptual Similarity Metrics based on male alice Deep Networks. Alexey Dosovitskiy*, ; Thomas Brox, University of Essay And The Freiburg. Dynamic Filter Networks.

Xu Jia*, KU Leuven; Bert De Brabandere, ; Tinne Tuytelaars, KU Leuven; Luc Van Gool, ETH Zurich. A Simple Practical Accelerated Method for Finite Sums. Aaron Defazio*, Ambiata. Barzilai-Borwein Step Size for male in wonderland, Stochastic Gradient Descent. Conghui Tan*, The Chinese University of Analysis of Etisalat’s Telecommunication Service HK; Shiqian Ma, ; Yu-Hong Dai, ; Yuqiu Qian, The University of alice in wonderland Hong Kong. On Graph Reconstruction via Empirical Risk Minimization: Fast Learning Rates and Scalability.

Guillaume Papa, Telecom ParisTech; Aurelien Bellet*, ; Stephan Clemencon, Optimal spectral transportation with application to revolution music transcription. Remi Flamary, ; Cedric Fevotte*, CNRS; Nicolas Courty, ; Valentin Emiya, Aix-Marseille University. Regularized Nonlinear Acceleration. Damien Scieur*, INRIA - ENS; Alexandre D'Aspremont, ; Francis Bach, SPALS: Fast Alternating Least Squares via Implicit Leverage Scores Sampling. Dehua Cheng*, Univ. of Southern California; Richard Peng, ; Yan Liu, ; Ioakeim Perros, Georgia Institute of male alice in wonderland Technology. Single-Image Depth Perception in the Wild. Weifeng Chen*, University of Essay Michigan; Zhao Fu, University of Michigan; Dawei Yang, University of Michigan; Jia Deng, Computational and alice in wonderland, Statistical Tradeoffs in Learning to Rank. Ashish Khetan*, University of Illinois Urbana-; Sewoong Oh,

Learning to puritan american Poke by Poking: Experiential Learning of Intuitive Physics. Pulkit Agrawal*, UC Berkeley; Ashvin Nair, UC Berkeley; Pieter Abbeel, ; Jitendra Malik, ; Sergey Levine, University of Washington. Online Convex Optimization with Unconstrained Domains and alice, Losses. Ashok Cutkosky*, Stanford University; Kwabena Boahen, Stanford University. An ensemble diversity approach to the quiet change supervised binary hashing. Miguel Carreira-Perpinan*, UC Merced; Ramin Raziperchikolaei, UC Merced. Efficient Globally Convergent Stochastic Optimization for in wonderland, Canonical Correlation Analysis. Weiran Wang*, ; Jialei Wang, University of Chicago; Dan Garber, ; Nathan Srebro, The Power of puritan american Adaptivity in male in wonderland, Identifying Statistical Alternatives. Kevin Jamieson*, UC Berkeley; Daniel Haas, ; Ben Recht,

On Explore-Then-Commit strategies. Aurelien Garivier, ; Tor Lattimore, ; Emilie Kaufmann*, Sublinear Time Orthogonal Tensor Decomposition. Zhao Song*, UT-Austin; David Woodruff, ; Huan Zhang, UC-Davis. DECOrrelated feature space partitioning for Essay, distributed sparse regression. Xiangyu Wang*, Duke University; David Dunson, Duke University; Chenlei Leng, University of Warwick. Deep Alternative Neural Networks: Exploring Contexts as Early as Possible for male alice, Action Recognition. Jinzhuo Wang*, PKU; Wenmin Wang, peking university; xiongtao Chen, peking university; Ronggang Wang, peking university; Wen Gao, peking university. Machine Translation Through Learning From a Communication Game. Di He*, Microsoft; Yingce Xia, USTC; Tao Qin, Microsoft; Liwei Wang, ; Nenghai Yu, USTC; Tie-Yan Liu, Microsoft; wei-Ying Ma, Microsoft. Dialog-based Language Learning.

Joint Line Segmentation and Essay on Happiness and the Light, Transcription for End-to-End Handwritten Paragraph Recognition. Theodore Bluche*, A2iA. Temporal Regularized Matrix Factorization for alice, High-dimensional Time Series Prediction. Hsiang-Fu Yu*, University of of Life Essay Texas at male in wonderland, Austin; Nikhil Rao, ; Inderjit Dhillon, Active Nearest-Neighbor Learning in of Etisalat’s Telecommunication Essay, Metric Spaces. Aryeh Kontorovich, ; Sivan Sabato*, Ben-Gurion University of the alice, Negev; Ruth Urner, MPI Tuebingen. Proximal Deep Structured Models. Shenlong Wang*, University of Toronto; Sanja Fidler, ; Raquel Urtasun, Faster Projection-free Convex Optimization over on Of China the Spectrahedron.

Bayesian Optimization with a Finite Budget: An Approximate Dynamic Programming Approach. Remi Lam*, MIT; Karen Willcox, MIT; David Wolpert, Learning Sound Representations from Unlabeled Video. Yusuf Aytar, MIT; Carl Vondrick*, MIT; Antonio Torralba, Weight Normalization: A Simple Reparameterization to alice in wonderland Accelerate Training of the quiet revolution change quebec Deep Neural Networks.

Tim Salimans*, ; Diederik Kingma, Efficient Second Order Online Learning by alice in wonderland Sketching. Haipeng Luo*, Princeton University; Alekh Agarwal, Microsoft; Nicolo Cesa-Bianchi, ; John Langford, Dynamic Mode Decomposition with Reproducing Kernels for Essay From, Koopman Spectral Analysis. Yoshinobu Kawahara*, Osaka University. Distributed Flexible Nonlinear Tensor Factorization.

Shandian Zhe*, Purdue University; Kai Zhang, Lawrence Berkeley Lab; Pengyuan Wang, Yahoo! Research; Kuang-chih Lee, ; Zenglin Xu, ; Alan Qi, ; Zoubin Ghahramani, The Robustness of male alice Estimator Composition. Pingfan Tang*, University of Utah; Jeff Phillips, University of Essay on Happiness and the Light Utah. Efficient and Robust Spiking Neural Circuit for male, Navigation Inspired by Echolocating Bats. Bipin Rajendran*, NJIT; Pulkit Tandon, IIT Bombay; Yash Malviya, IIT Bombay. PerforatedCNNs: Acceleration through Elimination of Redundant Convolutions. Michael Figurnov*, Skolkovo Inst. of Sc and about 84th Division, Tech; Aijan Ibraimova, Skolkovo Institute of Science and alice in wonderland, Technology; Dmitry P. Of Etisalat’s! Vetrov, ; Pushmeet Kohli,

Differential Privacy without Sensitivity. Kentaro Minami*, The University of in wonderland Tokyo; HItomi Arai, The University of Tokyo; Issei Sato, The University of about The History 84th Division Tokyo; Hiroshi Nakagawa, Optimal Cluster Recovery in the Labeled Stochastic Block Model. Se-Young Yun*, Los Alamos National Laboratory; Alexandre Proutiere, Even Faster SVD Decomposition Yet Without Agonizing Pain. Zeyuan Allen-Zhu*, Princeton University; Yuanzhi Li, Princeton University. An algorithm for alice, L1 nearest neighbor search via monotonic embedding.

Xinan Wang*, UCSD; Sanjoy Dasgupta, Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations. Kirthevasan Kandasamy*, CMU; Gautam Dasarathy, Carnegie Mellon University; Junier Oliva, ; Jeff Schneider, CMU; Barnabas Poczos, Linear-Memory and of Etisalat’s Telecommunication Service, Decomposition-Invariant Linearly Convergent Conditional Gradient Algorithm for male alice, Structured Polytopes. Dan Garber*, ; Ofer Meshi, Efficient Nonparametric Smoothness Estimation. Shashank Singh*, Carnegie Mellon University; Simon Du, Carnegie Mellon University; Barnabas Poczos, A Theoretically Grounded Application of of Life Essay Dropout in Recurrent Neural Networks. Yarin Gal*, University of Cambridge; Zoubin Ghahramani, Fast ?-free Inference of Simulation Models with Bayesian Conditional Density Estimation.

George Papamakarios*, University of Edinburgh; Iain Murray, University of male in wonderland Edinburgh. Direct Feedback Alignment Provides Learning In Deep Neural Networks. Arild Nokland*, None. Safe and revolution quebec, Efficient Off-Policy Reinforcement Learning. Remi Munos, Google DeepMind; Thomas Stepleton, Google DeepMind; Anna Harutyunyan, Vrije Universiteit Brussel; Marc Bellemare*, Google DeepMind. A Multi-Batch L-BFGS Method for male alice, Machine Learning. Albert Berahas*, Northwestern University; Jorge Nocedal, Northwestern University; Martin Takac, Lehigh University. Semiparametric Differential Graph Models. Pan Xu*, University of Service Virginia; Quanquan Gu, University of Virginia. Renyi Divergence Variational Inference.

Yingzhen Li*, University of Cambridge; Richard E. Turner, Doubly Convolutional Neural Networks. Shuangfei Zhai*, Binghamton University; Yu Cheng, IBM Research; Zhongfei Zhang, Binghamton University. Density Estimation via Discrepancy Based Adaptive Sequential Partition. Dangna Li*, Stanford university; Kun Yang, Google Inc; Wing Wong, Stanford university. How Deep is the Feature Analysis underlying Rapid Visual Categorization? Sven Eberhardt*, Brown University; Jonah Cader, Brown University; Thomas Serre, Variational Information Maximizing Exploration. Rein Houthooft*, Ghent University - iMinds; UC Berkeley; OpenAI; Xi Chen, UC Berkeley; OpenAI; Yan Duan, UC Berkeley; John Schulman, OpenAI; Filip De Turck, Ghent University - iMinds; Pieter Abbeel, Generalized Correspondence-LDA Models (GC-LDA) for Identifying Functional Regions in the Brain. Timothy Rubin*, Indiana University; Sanmi Koyejo, UIUC; Michael Jones, Indiana University; Tal Yarkoni, University of alice in wonderland Texas at Austin.

Solving Marginal MAP Problems with NP Oracles and puritan american, Parity Constraints. Yexiang Xue*, Cornell University; Zhiyuan Li, Tsinghua University; Stefano Ermon, ; Carla Gomes, Cornell University; Bart Selman, Multi-view Anomaly Detection via Robust Probabilistic Latent Variable Models. Tomoharu Iwata*, ; Makoto Yamada, Fast Stochastic Methods for Nonsmooth Nonconvex Optimization.

Sashank Jakkam Reddi*, Carnegie Mellon University; Suvrit Sra, MIT; Barnabas Poczos, ; Alexander J. Alice In Wonderland! Smola, Variance Reduction in Stochastic Gradient Langevin Dynamics. Kumar Dubey*, Carnegie Mellon University; Sashank Jakkam Reddi, Carnegie Mellon University; Sinead Williamson, ; Barnabas Poczos, ; Alexander J. How Did The Quiet Change! Smola, ; Eric Xing, Carnegie Mellon University. Regularization With Stochastic Transformations and male alice, Perturbations for Essay, Deep Semi-Supervised Learning. Mehdi Sajjadi*, University of male in wonderland Utah; Mehran Javanmardi, University of Analysis of Etisalat’s Service Essay Utah; Tolga Tasdizen, University of alice in wonderland Utah. Dense Associative Memory for Pattern Recognition.

Dmitry Krotov*, Institute for Advanced Study; John Hopfield, Princeton Neuroscience Institute. Causal Bandits: Learning Good Interventions via Causal Inference. Finnian Lattimore, Australian National University; Tor Lattimore*, ; Mark Reid, Refined Lower Bounds for on Happiness Light, Adversarial Bandits. Sebastien Gerchinovitz, ; Tor Lattimore*, Theoretical Comparisons of alice Positive-Unlabeled Learning against on Happiness the Dark and the Light Positive-Negative Learning. Gang Niu*, University of male alice in wonderland Tokyo; Marthinus du Plessis, ; Tomoya Sakai, ; Yao Ma, ; Masashi Sugiyama, RIKEN / University of puritan american Tokyo. Homotopy Smoothing for male alice, Non-Smooth Problems with Lower Complexity than $O(1/epsilon)$

Yi Xu*, The University of Iowa; Yan Yan, University of Technology Sydney; Qihang Lin, ; Tianbao Yang, University of Iowa. Finite-Sample Analysis of quebec Fixed-k Nearest Neighbor Density Functionals Estimators. Shashank Singh*, Carnegie Mellon University; Barnabas Poczos, A state-space model of male alice in wonderland cross-region dynamic connectivity in The Riddle Essay, MEG/EEG. Ying Yang*, Carnegie Mellon University; Elissa Aminoff, Carnegie Mellon University; Michael Tarr, Carnegie Mellon University; Robert Kass, Carnegie Mellon University. What Makes Objects Similar: A Unified Multi-Metric Learning Approach. Han-Jia Ye, ; De-Chuan Zhan*, ; Xue-Min Si, Nanjing University; Yuan Jiang, Nanjing University; Zhi-Hua Zhou, Adaptive Maximization of alice in wonderland Pointwise Submodular Functions With Budget Constraint.

Nguyen Viet Cuong*, National University of Singapore; Huan Xu, NUS. Dueling Bandits: Beyond Condorcet Winners to puritan General Tournament Solutions. Siddartha Ramamohan, Indian Institute of alice in wonderland Science; Arun Rajkumar, ; Shivani Agarwal*, Radcliffe Institute, Harvard. Local Similarity-Aware Deep Feature Embedding. Chen Huang*, Chinese University of the quiet quebec HongKong; Chen Change Loy, The Chinese University of HK; Xiaoou Tang, The Chinese University of male in wonderland Hong Kong. A Communication-Efficient Parallel Algorithm for Decision Tree. Qi Meng*, Peking University; Guolin Ke, Microsoft Research; Taifeng Wang, Microsoft Research; Wei Chen, Microsoft Research; Qiwei Ye, Microsoft Research; Zhi-Ming Ma, Academy of Mathematics and Systems Science, Chinese Academy of Sciences; Tie-Yan Liu, Microsoft Research.

Convex Two-Layer Modeling with Latent Structure. Vignesh Ganapathiraman, University Of Illinois at Essay on And The Of China, Chicago; Xinhua Zhang*, UIC; Yaoliang Yu, ; Junfeng Wen, UofA. Sampling for Bayesian Program Learning. Kevin Ellis*, MIT; Armando Solar-Lezama, MIT; Joshua Tenenbaum, Learning Kernels with Random Features. Aman Sinha*, Stanford University; John Duchi,

Optimal Tagging with Markov Chain Optimization. Nir Rosenfeld*, Hebrew University of alice Jerusalem; Amir Globerson, Tel Aviv University. Crowdsourced Clustering: Querying Edges vs Triangles. Ramya Korlakai Vinayak*, Caltech; Hassibi Babak, Caltech. Mixed vine copulas as joint models of spike counts and local field potentials. Arno Onken*, IIT; Stefano Panzeri, IIT. Achieving the KS threshold in the general stochastic block model with linearized acyclic belief propagation. Emmanuel Abbe*, ; Colin Sandon, Adaptive Concentration Inequalities for Sequential Decision Problems. Shengjia Zhao*, Tsinghua University; Enze Zhou, Tsinghua University; Ashish Sabharwal, Allen Institute for AI; Stefano Ermon, Fast mini-batch k-means by revolution change quebec nesting.

James Newling*, Idiap Research Institute; Francois Fleuret, Idiap Research Institute. Deep Learning Models of the male alice in wonderland, Retinal Response to Natural Scenes. Lane McIntosh*, Stanford University; Niru Maheswaranathan, Stanford University; Aran Nayebi, Stanford University; Surya Ganguli, Stanford; Stephen Baccus, Stanford University. Preference Completion from Partial Rankings. Suriya Gunasekar*, UT Austin; Sanmi Koyejo, UIUC; Joydeep Ghosh, UT Austin. Dynamic Network Surgery for Essay Google And The Government Of China, Efficient DNNs. Yiwen Guo*, Intel Labs China; Anbang Yao, ; Yurong Chen,

Learning a Metric Embedding for Face Recognition using the male, Multibatch Method. Oren Tadmor, OrCam; Tal Rosenwein, Orcam; Shai Shalev-Shwartz, OrCam; Yonatan Wexler*, OrCam; Amnon Shashua, OrCam. A Pseudo-Bayesian Algorithm for Analysis Telecommunication Essay, Robust PCA. Tae-Hyun Oh*, KAIST; David Wipf, ; Yasuyuki Matsushita, Osaka University; In So Kweon, KAIST. End-to-End Kernel Learning with Supervised Convolutional Kernel Networks. Julien Mairal*, Inria. Stochastic Variance Reduction Methods for Saddle-Point Problems. P. Balamurugan, ; Francis Bach*, Flexible Models for Microclustering with Applications to Entity Resolution. Brenda Betancourt, Duke University; Giacomo Zanella, The University of male alice Warick; Jeffrey Miller, Duke University; Hanna Wallach, Microsoft Research; Abbas Zaidi, Duke University; Rebecca C. Analysis Of Etisalat’s Service! Steorts*, Duke University. Catching heuristics are optimal control policies.

Boris Belousov*, TU Darmstadt; Gerhard Neumann, ; Constantin Rothkopf, ; Jan Peters, Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian. Victor Picheny, Institut National de la Recherche Agronomique; Robert Gramacy*, ; Stefan Wild, Argonne National Lab; Sebastien Le Digabel, Ecole Polytechnique de Montreal. Adaptive Neural Compilation. Rudy Bunel*, Oxford University; Alban Desmaison, Oxford; M. In Wonderland! Pawan Kumar, University of puritan american Oxford; Pushmeet Kohli, ; Philip Torr, Synthesis of male MCMC and Belief Propagation. Sung-Soo Ahn*, KAIST; Misha Chertkov, Los Alamos National Laboratory; Jinwoo Shin, KAIST.

Learning Treewidth-Bounded Bayesian Networks with Thousands of Variables. Mauro Scanagatta*, Idsia; Giorgio Corani, Idsia; Cassio Polpo de Campos, Queen's University Belfast; Marco Zaffalon, IDSIA. Unifying Count-Based Exploration and Essay The History of the 84th Infantry, Intrinsic Motivation. Marc Bellemare*, Google DeepMind; Srinivasan Sriram, ; Georg Ostrovski, Google DeepMind; Tom Schaul, ; David Saxton, Google DeepMind; Remi Munos, Google DeepMind. Large Margin Discriminant Dimensionality Reduction in Prediction Space. Mohammad Saberian*, Netflix; Jose Costa Pereira, UC San Diego; Nuno Nvasconcelos, UC San Diego. Stochastic Structured Prediction under Bandit Feedback.

Artem Sokolov, Heidelberg University; Julia Kreutzer, Heidelberg University; Stefan Riezler*, Heidelberg University. Simple and male, Efficient Weighted Minwise Hashing. Anshumali Shrivastava*, Rice University. Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and The Riddle of Life, Level-Set Estimation. Ilija Bogunovic*, EPFL Lausanne; Jonathan Scarlett, ; Andreas Krause, ; Volkan Cevher, Structured Sparse Regression via Greedy Hard Thresholding. Prateek Jain, Microsoft Research; Nikhil Rao*, ; Inderjit Dhillon, Understanding Probabilistic Sparse Gaussian Process Approximations.

Matthias Bauer*, University of Cambridge; Mark van der Wilk, University of male in wonderland Cambridge; Carl Rasmussen, University of how did quebec Cambridge. SEBOOST - Boosting Stochastic Learning Using Subspace Optimization Techniques. Elad Richardson*, Technion; Rom Herskovitz, ; Boris Ginsburg, ; Michael Zibulevsky, Long-Term Trajectory Planning Using Hierarchical Memory Networks. Stephan Zheng*, Caltech; Yisong Yue, ; Patrick Lucey, Stats. Learning Tree Structured Potential Games. Vikas Garg*, MIT; Tommi Jaakkola,

Observational-Interventional Priors for Dose-Response Learning. Learning from Rational Behavior: Predicting Solutions to in wonderland Unknown Linear Programs. Shahin Jabbari*, University of Essay The History 84th Division Pennsylvania; Ryan Rogers, University of male alice Pennsylvania; Aaron Roth, ; Steven Wu, University of on Happiness and the Light Pennsylvania. Identification and alice, Overidentification of Analysis of Etisalat’s Linear Structural Equation Models. Adaptive Skills Adaptive Partitions (ASAP) Daniel Mankowitz*, Technion; Timothy Mann, Google DeepMind; Shie Mannor, Technion. Multiple-Play Bandits in male alice, the Position-Based Model. Paul Lagree*, Universite Paris Sud; Claire Vernade, Universite Paris Saclay; Olivier Cappe, Optimal Black-Box Reductions Between Optimization Objectives.

Zeyuan Allen-Zhu*, Princeton University; Elad Hazan, On Valid Optimal Assignment Kernels and Essay From the Dark, Applications to in wonderland Graph Classification. Nils Kriege*, TU Dortmund; Pierre-Louis Giscard, University of York; Richard Wilson, University of York. Robustness of revolution change classifiers: from adversarial to male alice in wonderland random noise. Alhussein Fawzi, ; Seyed-Mohsen Moosavi-Dezfooli*, EPFL; Pascal Frossard, EPFL. A Non-convex One-Pass Framework for Factorization Machines and Rank-One Matrix Sensing. Exploiting the of Etisalat’s Service Essay, Structure: Stochastic Gradient Methods Using Raw Clusters. Zeyuan Allen-Zhu*, Princeton University; Yang Yuan, Cornell University; Karthik Sridharan, University of male alice in wonderland Pennsylvania. Combinatorial Multi-Armed Bandit with General Reward Functions. Wei Chen*, ; Wei Hu, Princeton University; Fu Li, The University of Texas at Austin; Jian Li, Tsinghua University; Yu Liu, Tsinghua University; Pinyan Lu, Shanghai University of Finance and puritan, Economics.

Boosting with Abstention. Corinna Cortes, ; Giulia DeSalvo*, ; Mehryar Mohri, Regret of male in wonderland Queueing Bandits. Subhashini Krishnasamy, The University of how did the quiet change Texas at Austin; Rajat Sen, The University of male Texas at on Happiness From and the, Austin; Ramesh Johari, ; Sanjay Shakkottai*, The University of Texas at male alice, Aus. Dale Schuurmans*, ; Martin Zinkevich, Google. Globally Optimal Training of 84th Infantry Generalized Polynomial Neural Networks with Nonlinear Spectral Methods. Antoine Gautier*, Saarland University; Quynh Nguyen, Saarland University; Matthias Hein, Saarland University. Learning Volumetric 3D Object Reconstruction from male alice in wonderland Single-View with Projective Transformations. Xinchen Yan*, University of Michigan; Jimei Yang, ; Ersin Yumer, Adobe Research; Yijie Guo, University of american Michigan; Honglak Lee, University of male alice in wonderland Michigan. A Credit Assignment Compiler for how did the quiet change quebec, Joint Prediction.

Kai-Wei Chang*, ; He He, University of Maryland; Stephane Ross, Google; Hal III, ; John Langford, Accelerating Stochastic Composition Optimization. Reward Augmented Maximum Likelihood for male alice in wonderland, Neural Structured Prediction. Mohammad Norouzi*, ; Dale Schuurmans, ; Samy Bengio, ; zhifeng Chen, ; Navdeep Jaitly, ; Mike Schuster, ; Yonghui Wu, Consistent Kernel Mean Estimation for Infantry, Functions of Random Variables. Adam Scibior*, University of male alice Cambridge; Carl-Johann Simon-Gabriel, MPI Tuebingen; Iliya Tolstikhin, ; Bernhard Schoelkopf, Towards Unifying Hamiltonian Monte Carlo and Slice Sampling. Yizhe Zhang*, Duke university; Xiangyu Wang, Duke University; Changyou Chen, ; Ricardo Henao, ; Kai Fan, Duke university; Lawrence Carin, Scalable Adaptive Stochastic Optimization Using Random Projections. Gabriel Krummenacher*, ETH Zurich; Brian Mcwilliams, Disney Research; Yannic Kilcher, ETH Zurich; Joachim Buhmann, ETH Zurich; Nicolai Meinshausen,

Variational Inference in Mixed Probabilistic Submodular Models. Josip Djolonga, ETH Zurich; Sebastian Tschiatschek*, ETH Zurich; Andreas Krause, Correlated-PCA: Principal Components' Analysis when Data and Noise are Correlated. Namrata Vaswani*, ; Han Guo, Iowa State University. The Multi-fidelity Multi-armed Bandit. Kirthevasan Kandasamy*, CMU; Gautam Dasarathy, Carnegie Mellon University; Barnabas Poczos, ; Jeff Schneider, CMU. Anchor-Free Correlated Topic Modeling: Identifiability and Algorithm. Kejun Huang*, University of about The History 84th Infantry Division Minnesota; Xiao Fu, University of Minnesota; Nicholas Sidiropoulos, University of alice Minnesota.

Bootstrap Model Aggregation for Distributed Statistical Learning. JUN HAN, Dartmouth College; Qiang Liu*, A scalable end-to-end Gaussian process adapter for american, irregularly sampled time series classification. Steven Cheng-Xian Li*, UMass Amherst; Benjamin Marlin, A Bandit Framework for Strategic Regression. Yang Liu*, Harvard University; Yiling Chen, Architectural Complexity Measures of Recurrent Neural Networks. Saizheng Zhang*, University of alice in wonderland Montreal; Yuhuai Wu, University of Toronto; Tong Che, IHES; Zhouhan Lin, University of Montreal; Roland Memisevic, University of about The History of the Montreal; Ruslan Salakhutdinov, University of in wonderland Toronto; Yoshua Bengio, U. How Did The Quiet Change! Montreal. Statistical Inference for male in wonderland, Cluster Trees.

Jisu Kim*, Carnegie Mellon University; Yen-Chi Chen, Carnegie Mellon University; Sivaraman Balakrishnan, Carnegie Mellon University; Alessandro Rinaldo, Carnegie Mellon University; Larry Wasserman, Carnegie Mellon University. Contextual-MDPs for PAC Reinforcement Learning with Rich Observations. Akshay Krishnamurthy*, ; Alekh Agarwal, Microsoft; John Langford, Improved Deep Metric Learning with Multi-class N-pair Loss Objective. Only H is left: Near-tight Episodic PAC RL. Christoph Dann*, Carnegie Mellon University; Emma Brunskill, Carnegie Mellon University Unsupervised Learning of Essay about of the Infantry Division Spoken Language with Visual Context. David Harwath*, MIT CSAIL; Antonio Torralba, MIT CSAIL; James Glass, MIT CSAIL.

Low-Rank Regression with Tensor Responses. Guillaume Rabusseau*, Aix-Marseille University; Hachem Kadri, PAC-Bayesian Theory Meets Bayesian Inference. Pascal Germain*, ; Francis Bach, ; Alexandre Lacoste, ; Simon Lacoste-Julien, INRIA. Data Poisoning Attacks on male alice Factorization-Based Collaborative Filtering. Bo Li*, Vanderbilt University; Yining Wang, Carnegie Mellon University; Aarti Singh, Carnegie Mellon University; yevgeniy Vorobeychik, Vanderbilt University. Learned Region Sparsity and Analysis Telecommunication Service, Diversity Also Predicts Visual Attention. Zijun Wei*, Stony Brook; Hossein Adeli, ; Minh Hoai, ; Gregory Zelinsky, ; Dimitris Samaras,

End-to-End Goal-Driven Web Navigation. Rodrigo Frassetto Nogueira*, New York University; Kyunghyun Cho, University of Montreal. Automated scalable segmentation of neurons from male multispectral images. Uygar Sumbul*, Columbia University; Douglas Roossien, University of The Riddle of Life Michigan, Ann Arbor; Dawen Cai, University of Michigan, Ann Arbor; John Cunningham, Columbia University; Liam Paninski, Privacy Odometers and Filters: Pay-as-you-Go Composition. Ryan Rogers*, University of male alice Pennsylvania; Salil Vadhan, Harvard University; Aaron Roth, ; Jonathan Robert Ullman, Minimax Estimation of Maximal Mean Discrepancy with Radial Kernels. Iliya Tolstikhin*, ; Bharath Sriperumbudur, ; Bernhard Schoelkopf, Adaptive optimal training of on Google animal behavior. Ji Hyun Bak*, Princeton University; Jung Yoon Choi, ; Ilana Witten, ; Jonathan Pillow, Hierarchical Object Representation for alice in wonderland, Open-Ended Object Category Learning and Recognition.

Hamidreza Kasaei*, IEETA, University of Aveiro. Relevant sparse codes with variational information bottleneck. Matthew Chalk*, IST Austria; Olivier Marre, Institut de la vision; Gasper Tkacik, Institute of about of the 84th Infantry Science and male alice, Technology Austria. Combinatorial Energy Learning for on Google And The Government Of China, Image Segmentation. Jeremy Maitin-Shepard*, Google; Viren Jain, Google; Michal Januszewski, Google; Peter Li, ; Pieter Abbeel, Orthogonal Random Features. Felix Xinnan Yu*, ; Ananda Theertha Suresh, ; Krzysztof Choromanski, ; Dan Holtmann-Rice, ; Sanjiv Kumar, Google. Fast Active Set Methods for Online Spike Inference from male in wonderland Calcium Imaging.

Johannes Friedrich*, Columbia University; Liam Paninski, Diffusion-Convolutional Neural Networks. James Atwood*, UMass Amherst. Bayesian latent structure discovery from Analysis of Etisalat’s Telecommunication Service Essay multi-neuron recordings. Scott Linderman*, ; Ryan Adams, ; Jonathan Pillow, A Probabilistic Programming Approach To Probabilistic Data Analysis. Feras Saad*, MIT; Vikash Mansinghka, MIT. A Non-parametric Learning Method for Confidently Estimating Patient's Clinical State and male in wonderland, Dynamics. William Hoiles*, University of California, Los ; Mihaela Van Der Schaar,

Inference by Reparameterization in Service, Neural Population Codes. RAJKUMAR VASUDEVA RAJU, Rice University; Xaq Pitkow*, Tensor Switching Networks. Chuan-Yung Tsai*, ; Andrew Saxe, ; David Cox, Stochastic Gradient Richardson-Romberg Markov Chain Monte Carlo. Alain Durmus, Telecom ParisTech; Umut Simsekli*, ; Eric Moulines, Ecole Polytechnique; Roland Badeau, Telecom ParisTech; Gael Richard, Telecom ParisTech. Coordinate-wise Power Method. Qi Lei*, UT AUSTIN; Kai Zhong, UT AUSTIN; Inderjit Dhillon, Learning Influence Functions from Incomplete Observations.

Xinran He*, USC; Ke Xu, USC; David Kempe, USC; Yan Liu, Learning Structured Sparsity in in wonderland, Deep Neural Networks. Wei Wen*, University of Pittsburgh; Chunpeng Wu, University of Pittsburgh; Yandan Wang, University of puritan american Pittsburgh; Yiran Chen, University of male alice in wonderland Pittsburgh; Hai Li, University of Pittsburg. Sample Complexity of Automated Mechanism Design. Nina Balcan, ; Tuomas Sandholm, Carnegie Mellon University; Ellen Vitercik*, Carnegie Mellon University. Short-Dot: Computing Large Linear Transforms Distributedly Using Coded Short Dot Products. SANGHAMITRA DUTTA*, Carnegie Mellon University; Viveck Cadambe, Pennsylvania State University; Pulkit Grover, Carnegie Mellon University. Umut Guclu*, Radboud University; Jordy Thielen, Radboud University; Michael Hanke, Otto-von-Guericke University Magdeburg; Marcel Van Gerven, Radboud University. Learning Transferrable Representations for Unsupervised Domain Adaptation. Ozan Sener*, Cornell University; Hyun Oh Song, Google Research; Ashutosh Saxena, Brain of Analysis of Etisalat’s Service Essay Things; Silvio Savarese, Stanford University.

Stochastic Multiple Choice Learning for male in wonderland, Training Diverse Deep Ensembles. Stefan Lee*, Indiana University; Senthil Purushwalkam, Carnegie Mellon; Michael Cogswell, Virginia Tech; Viresh Ranjan, Virginia Tech; David Crandall, Indiana University; Dhruv Batra, Active Learning from on Happiness the Dark Light Imperfect Labelers. Songbai Yan*, University of California, San Diego; Kamalika Chaudhuri, University of in wonderland California, San Diego; Tara Javidi, University of puritan California, San Diego. Learning to male Communicate with Deep Multi-Agent Reinforcement Learning. Jakob Foerster*, University of Oxford; Yannis Assael, University of Essay of the 84th Oxford; Nando de Freitas, University of Oxford; Shimon Whiteson,

Value Iteration Networks. Aviv Tamar*, ; Sergey Levine, ; Pieter Abbeel, ; Yi Wu, UC Berkeley; Garrett Thomas, UC Berkeley. Blind Regression: Nonparametric Regression for Latent Variable Models via Collaborative Filtering. Dogyoon Song*, MIT; Christina Lee, MIT; Yihua Li, MIT; Devavrat Shah, On the male, Recursive Teaching Dimension of The Riddle of Life VC Classes. Bo Tang*, University of Oxford; Xi Chen, Columbia University; Yu Cheng, U of Southern California. InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets. Xi Chen*, UC Berkeley; OpenAI; Yan Duan, UC Berkeley; Rein Houthooft, Ghent University - iMinds; UC Berkeley; OpenAI; John Schulman, OpenAI; Ilya Sutskever, ; Pieter Abbeel,

Hardness of Online Sleeping Combinatorial Optimization Problems. Satyen Kale*, ; Chansoo Lee, ; David Pal, Mixed Linear Regression with Multiple Components. Kai Zhong*, UT AUSTIN; Prateek Jain, Microsoft Research; Inderjit Dhillon, Sequential Neural Models with Stochastic Layers. Marco Fraccaro*, DTU; Soren Sonderby, KU; Ulrich Paquet, ; Ole Winther, DTU. Stochastic Gradient Methods for alice, Distributionally Robust Optimization with f-divergences.

Hongseok Namkoong*, Stanford University; John Duchi, Minimizing Quadratic Functions in how did revolution change, Constant Time. Kohei Hayashi*, AIST; Yuichi Yoshida, NII. Improved Techniques for male alice in wonderland, Training GANs. Tim Salimans*, ; Ian Goodfellow, OpenAI; Wojciech Zaremba, OpenAI; Vicki Cheung, OpenAI; Alec Radford, OpenAI; Xi Chen, UC Berkeley; OpenAI. DeepMath - Deep Sequence Models for Premise Selection. Geoffrey Irving*, ; Christian Szegedy, ; Alexander Alemi, Google; Francois Chollet, ; Josef Urban, Czech Technical University in Prague. Learning Multiagent Communication with Backpropagation. Sainbayar Sukhbaatar, NYU; Arthur Szlam, ; Rob Fergus*, New York University Toward Deeper Understanding of of Life Essay Neural Networks: The Power of alice in wonderland Initialization and a Dual View on puritan Expressivity. Amit Daniely*, ; Roy Frostig, Stanford University; Yoram Singer, Google.

Learning the Number of male alice Neurons in Deep Networks. Jose Alvarez*, NICTA; Mathieu Salzmann, EPFL. Finding significant combinations of features in the presence of categorical covariates. Laetitia Papaxanthos*, ETH Zurich; Felipe Llinares, ETH Zurich; Dean Bodenham, ETH Zurich; Karsten Borgwardt, Examples are not Enough, Learn to how did the quiet change quebec Criticize! Model Criticism for alice in wonderland, Interpretable Machine Learning. Been Kim*, ; Rajiv Khanna, UT Austin; Sanmi Koyejo, UIUC. Optimistic Bandit Convex Optimization. Scott Yang*, New York University; Mehryar Mohri,

Safe Policy Improvement by Essay and the Light Minimizing Robust Baseline Regret. Mohamad Ghavamzadeh*, ; Marek Petrik, ; Yinlam Chow, Stanford University. Graphons, mergeons, and so on! Justin Eldridge*, The Ohio State University; Mikhail Belkin, ; Yusu Wang, The Ohio State University. Hierarchical Clustering via Spreading Metrics. Aurko Roy*, Georgia Tech; Sebastian Pokutta, GeorgiaTech. Learning Bayesian networks with ancestral constraints. Eunice Yuh-Jie Chen*, UCLA; Yujia Shen, ; Arthur Choi, ; Adnan Darwiche, Pruning Random Forests for in wonderland, Prediction on Essay a Budget. Feng Nan*, Boston University; Joseph Wang, Boston University; Venkatesh Saligrama,

Clustering with Bregman Divergences: an Asymptotic Analysis. Chaoyue Liu*, The Ohio State University; Mikhail Belkin, Variational Autoencoder for male in wonderland, Deep Learning of Images, Labels and Captions. Yunchen Pu*, Duke University; Zhe Gan, Duke; Ricardo Henao, ; Xin Yuan, Bell Labs; chunyuan Li, Duke; Andrew Stevens, Duke University; Lawrence Carin, Encode, Review, and Essay about The History of the Infantry Division, Decode: Reviewer Module for Caption Generation. Zhilin Yang*, Carnegie Mellon University; Ye Yuan, Carnegie Mellon University; Yuexin Wu, Carnegie Mellon University; William Cohen, Carnegie Mellon University; Ruslan Salakhutdinov, University of male in wonderland Toronto.

Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm. Qiang Liu*, ; Dilin Wang, Dartmouth College. A Bio-inspired Redundant Sensing Architecture. Anh Tuan Nguyen*, University of about The History of the 84th Division Minnesota; Jian Xu, University of Minnesota; Zhi Yang, University of male in wonderland Minnesota. Contextual semibandits via supervised learning oracles. Akshay Krishnamurthy*, ; Alekh Agarwal, Microsoft; Miro Dudik, Blind Attacks on Machine Learners. Alex Beatson*, Princeton University; Zhaoran Wang, Princeton University; Han Liu, Universal Correspondence Network. Christopher Choy*, Stanford University; Manmohan Chandraker, NEC Labs America; JunYoung Gwak, Stanford University; Silvio Savarese, Stanford University.

Satisfying Real-world Goals with Dataset Constraints. Gabriel Goh*, UC Davis; Andy Cotter, ; Maya Gupta, ; Michael Friedlander, UC Davis. Deep Learning for american, Predicting Human Strategic Behavior. Jason Hartford*, University of male alice in wonderland British Columbia; Kevin Leyton-Brown, ; James Wright, University of British Columbia. Phased Exploration with Greedy Exploitation in how did revolution change quebec, Stochastic Combinatorial Partial Monitoring Games. Sougata Chaudhuri*, University of male in wonderland Michigan ; Ambuj Tewari, University of on Google And The Michigan. Eliciting and Aggregating Categorical Data. Yiling Chen, ; Rafael Frongillo, ; Chien-Ju Ho*,

Measuring the male alice, reliability of Telecommunication Service Essay MCMC inference with Bidirectional Monte Carlo. Roger Grosse, ; Siddharth Ancha, University of in wonderland Toronto; Daniel Roy*, Breaking the about The History, Bandwidth Barrier: Geometrical Adaptive Entropy Estimation. Weihao Gao, UIUC; Sewoong Oh*, ; Pramod Viswanath, UIUC. Selective inference for male alice in wonderland, group-sparse linear models. Fan Yang, University of and the Chicago; Rina Foygel Barber*, ; Prateek Jain, Microsoft Research; John Lafferty, Graph Clustering: Block-models and model free results. Yali Wan*, University of alice in wonderland Washington; Marina Meila, University of Essay Google Of China Washington. Maximizing Influence in alice, an Ising Network: A Mean-Field Optimal Solution. Christopher Lynn*, University of puritan Pennsylvania; Dan Lee , University of in wonderland Pennsylvania.

Hypothesis Testing in Essay on Of China, Unsupervised Domain Adaptation with Applications in Neuroscience. Hao Zhou, University of Wisconsin Madiso; Vamsi Ithapu*, University of Wisconsin Madison; Sathya Ravi, University of Wisconsin Madiso; Vikas Singh, UW Madison; Grace Wahba, University of Wisconsin Madison; Sterling Johnson, University of Wisconsin Madison. Geometric Dirichlet Means Algorithm for alice, Topic Inference. Mikhail Yurochkin*, University of Michigan; Long Nguyen, Structured Prediction Theory Based on Factor Graph Complexity. Corinna Cortes, ; Vitaly Kuznetsov*, Courant Institute; Mehryar Mohri, ; Scott Yang, New York University. Improved Dropout for Shallow and american, Deep Learning. Zhe Li, The University of male Iowa; Boqing Gong, University of Essay about Infantry Division Central Florida; Tianbao Yang*, University of male alice in wonderland Iowa. Constraints Based Convex Belief Propagation. Yaniv Tenzer*, The Hebrew University; Alexander Schwing, ; Kevin Gimpel, ; Tamir Hazan,

Error Analysis of Generalized Nystrom Kernel Regression. Hong Chen, University of of Etisalat’s Telecommunication Service Texas; Haifeng Xia, Huazhong Agricultural University; Heng Huang*, University of alice in wonderland Texas Arlington. A Probabilistic Framework for Telecommunication Service Essay, Deep Learning. Ankit Patel, Baylor College of male alice in wonderland Medicine; Rice University; Tan Nguyen*, Rice University; Richard Baraniuk, General Tensor Spectral Co-clustering for Essay The History of the 84th Division, Higher-Order Data. Tao Wu*, Purdue University; Austin Benson, Stanford University; David Gleich,

Cyclades: Conflict-free Asynchronous Machine Learning. Xinghao Pan*, UC Berkeley; Stephen Tu, UC Berkeley; Maximilian Lam, UC Berkeley; Dimitris Papailiopoulos, ; Ce Zhang, Stanford; Michael Jordan, ; Kannan Ramchandran, ; Christopher Re, ; Ben Recht, Single Pass PCA of Matrix Products. Shanshan Wu*, UT Austin; Srinadh Bhojanapalli, TTI Chicago; Sujay Sanghavi, ; Alexandros G. Dimakis, Stochastic Variational Deep Kernel Learning. Andrew Wilson*, Carnegie Mellon University; Zhiting Hu, Carnegie Mellon University; Ruslan Salakhutdinov, University of male in wonderland Toronto; Eric Xing, Carnegie Mellon University. Interaction Screening: Efficient and american, Sample-Optimal Learning of male Ising Models. Marc Vuffray*, Los Alamos National Laboratory; Sidhant Misra, Los Alamos National Laboratory; Andrey Lokhov, Los Alamos National Laboratory; Misha Chertkov, Los Alamos National Laboratory. Long-term Causal Effects via Behavioral Game Theory.

Panos Toulis*, University of Chicago; David Parkes, Harvard University. Measuring Neural Net Robustness with Constraints. Osbert Bastani*, Stanford University; Yani Ioannou, University of Cambridge; Leonidas Lampropoulos, University of Pennsylvania; Dimitrios Vytiniotis, Microsoft Research; Aditya Nori, Microsoft Research; Antonio Criminisi, Reshaped Wirtinger Flow for Solving Quadratic Systems of of Etisalat’s Essay Equations. Huishuai Zhang*, Syracuse University; Yingbin Liang, Syracuse University. Nearly Isometric Embedding by Relaxation.

James McQueen*, University of male Washington; Marina Meila, University of Washington; Dominique Joncas, Google. Probabilistic Inference with Generating Functions for Poisson Latent Variable Models. Kevin Winner*, UMass CICS; Daniel Sheldon, Causal meets Submodular: Subset Selection with Directed Information. Yuxun Zhou*, UC Berkeley; Costas Spanos,

Depth from a Single Image by Light Harmonizing Overcomplete Local Network Predictions. Ayan Chakrabarti*, ; Jingyu Shao, UCLA; Greg Shakhnarovich, Deep Neural Networks with Inexact Matching for male, Person Re-Identification. Arulkumar Subramaniam, IIT Madras; Moitreya Chatterjee*, IIT Madras; Anurag Mittal, IIT Madras. Global Analysis of Expectation Maximization for Mixtures of Essay of the 84th Two Gaussians.

Ji Xu, Columbia university; Daniel Hsu*, ; Arian Maleki, Columbia University. Estimating the class prior and male alice in wonderland, posterior from Google Government noisy positives and alice in wonderland, unlabeled data. Shanatnu Jain*, Indiana University; Martha White, ; Predrag Radivojac, Kronecker Determinantal Point Processes. Zelda Mariet*, MIT; Suvrit Sra, MIT. Finite Sample Prediction and Recovery Bounds for Analysis of Etisalat’s, Ordinal Embedding. Lalit Jain*, University of male alice Wisconsin-Madison; Kevin Jamieson, UC Berkeley; Robert Nowak, University of Essay on Happiness and the Light Wisconsin Madison. Feature-distributed sparse regression: a screen-and-clean approach.

Jiyan Yang*, Stanford University; Michael Mahoney, ; Michael Saunders, Stanford University; Yuekai Sun, University of Michigan. Learning Bound for Parameter Transfer Learning. Wataru Kumagai*, Kanagawa University. Learning under uncertainty: a comparison between R-W and Bayesian approach. He Huang*, LIBR; Martin Paulus, LIBR. Bi-Objective Online Matching and Submodular Allocations. Hossein Esfandiari*, University of male Maryland; Nitish Korula, Google Research; Vahab Mirrokni, Google. Quantized Random Projections and of Etisalat’s Telecommunication Service, Non-Linear Estimation of male alice Cosine Similarity. Ping Li, ; Michael Mitzenmacher, Harvard University; Martin Slawski*, The non-convex Burer-Monteiro approach works on smooth semidefinite programs. Nicolas Boumal, ; Vlad Voroninski*, MIT; Afonso Bandeira,

Dimensionality Reduction of Massive Sparse Datasets Using Coresets. Dan Feldman, ; Mikhail Volkov*, MIT; Daniela Rus, MIT. Using Social Dynamics to Make Individual Predictions: Variational Inference with Stochastic Kinetic Model. Zhen Xu*, SUNY at Buffalo; Wen Dong, ; Sargur Srihari, Supervised learning through the lens of compression. Ofir David*, Technion - Israel institute of technology; Shay Moran, Technion - Israel institue of Technology; Amir Yehudayoff, Technion - Israel institue of Technology.

Generative Shape Models: Joint Text Recognition and how did the quiet quebec, Segmentation with Very Little Training Data. Xinghua Lou*, Vicarious FPC Inc; Ken Kansky, ; Wolfgang Lehrach, ; CC Laan, ; Bhaskara Marthi, ; D. Male Alice In Wonderland! Scott Phoenix, ; Dileep George, Image Restoration Using Very Deep Convolutional Encoder-Decoder Networks with Symmetric Skip Connections. Xiao-Jiao Mao, Nanjing University; Chunhua Shen*, ; Yu-Bin Yang, Object based Scene Representations using Fisher Scores of Essay Google And The Of China Local Subspace Projections. Mandar Dixit*, UC San Diego; Nuno Vasconcelos, Active Learning with Oracle Epiphany. Tzu-Kuo Huang, Microsoft Research; Lihong Li, Microsoft Research; Ara Vartanian, University of Wisconsin-Madison; Saleema Amershi, Microsoft; Xiaojin Zhu*, Statistical Inference for Pairwise Graphical Models Using Score Matching. Ming Yu*, The University of male in wonderland Chicago; Mladen Kolar, ; Varun Gupta, University of Essay Government Of China Chicago. Improved Error Bounds for Tree Representations of Metric Spaces.

Samir Chowdhury*, The Ohio State University; Facundo Memoli, ; Zane Smith, Can Peripheral Representations Improve Clutter Metrics on Complex Scenes? Arturo Deza*, UCSB; Miguel Eckstein, UCSB. On Multiplicative Integration with Recurrent Neural Networks. Yuhuai Wu*, University of Toronto; Saizheng Zhang, University of Montreal; ying Zhang, University of Montreal; Yoshua Bengio, U. Montreal; Ruslan Salakhutdinov, University of Toronto. Learning HMMs with Nonparametric Emissions via Spectral Decompositions of in wonderland Continuous Matrices. Kirthevasan Kandasamy*, CMU; Maruan Al-Shedivat, CMU; Eric Xing, Carnegie Mellon University.

Regret Bounds for Non-decomposable Metrics with Missing Labels. Nagarajan Natarajan*, Microsoft Research Bangalore; Prateek Jain, Microsoft Research. Robust k-means: a Theoretical Revisit. ALEXANDROS GEORGOGIANNIS*, TECHNICAL UNIVERSITY OF CRETE. Bayesian optimization for automated model selection. Gustavo Malkomes, Washington University; Charles Schaff, Washington University in Essay on Google And The, St. Louis; Roman Garnett*, A Probabilistic Model of Social Decision Making based on Reward Maximization. Koosha Khalvati*, University of Washington; Seongmin Park, Cognitive Neuroscience Center; Jean-Claude Dreher, Centre de Neurosciences Cognitives; Rajesh Rao, University of male alice in wonderland Washington. Balancing Suspense and Surprise: Timely Decision Making with Endogenous Information Acquisition.

Ahmed Alaa*, UCLA; Mihaela Van Der Schaar, Fast and of Etisalat’s Telecommunication Service, Flexible Monotonic Functions with Ensembles of Lattices. Mahdi Fard, ; Kevin Canini, ; Andy Cotter, ; Jan Pfeifer, Google; Maya Gupta*, Conditional Generative Moment-Matching Networks. Yong Ren, Tsinghua University; Jun Zhu*, ; Jialian Li, Tsinghua University; Yucen Luo, Stochastic Gradient MCMC with Stale Gradients. Changyou Chen*, ; Nan Ding, Google; chunyuan Li, Duke; Yizhe Zhang, Duke university; Lawrence Carin, Composing graphical models with neural networks for alice in wonderland, structured representations and fast inference. Matthew Johnson, ; David Duvenaud*, ; Alex Wiltschko, Harvard University and Essay about 84th Infantry, Twitter; Ryan Adams, ; Sandeep Datta, Harvard Medical School. Noise-Tolerant Life-Long Matrix Completion via Adaptive Sampling. Nina Balcan, ; Hongyang Zhang*, CMU.

Combinatorial semi-bandit with known covariance. Remy Degenne*, Universite Paris Diderot; Vianney Perchet, Matrix Completion has No Spurious Local Minimum. Rong Ge, ; Jason Lee, UC Berkeley; Tengyu Ma*, Princeton University. The Multiscale Laplacian Graph Kernel.

Risi Kondor*, ; Horace Pan, UChicago. Adaptive Averaging in Accelerated Descent Dynamics. Walid Krichene*, UC Berkeley; Alexandre Bayen, UC Berkeley; Peter Bartlett, Sub-sampled Newton Methods with Non-uniform Sampling. Peng Xu*, Stanford University; Jiyan Yang, Stanford University; Farbod Roosta-Khorasani, University of California Berkeley; Christopher Re, ; Michael Mahoney, Stochastic Gradient Geodesic MCMC Methods. Chang Liu*, Tsinghua University; Jun Zhu, ; Yang Song, Stanford University. Variational Bayes on Monte Carlo Steroids. Aditya Grover*, Stanford University; Stefano Ermon,

Showing versus doing: Teaching by alice demonstration. Mark Ho*, Brown University; Michael L. Littman, ; James MacGlashan, Brown University; Fiery Cushman, Harvard University; Joe Austerweil, Combining Fully Convolutional and Recurrent Neural Networks for Essay about The History of the, 3D Biomedical Image Segmentation. Jianxu Chen*, University of Notre Dame; Lin Yang, University of male in wonderland Notre Dame; Yizhe Zhang, University of on Of China Notre Dame; Mark Alber, University of Notre Dame; Danny Chen, University of alice in wonderland Notre Dame. Maximization of Approximately Submodular Functions. Thibaut Horel*, Harvard University; Yaron Singer, A Comprehensive Linear Speedup Analysis for Asynchronous Stochastic Parallel Optimization from Zeroth-Order to Analysis of Etisalat’s Service First-Order. Xiangru Lian, University of Rochester; Huan Zhang, ; Cho-Jui Hsieh, ; Yijun Huang, ; Ji Liu*,

Learning Infinite RBMs with Frank-Wolfe. Wei Ping*, UC Irvine; Qiang Liu, ; Alexander Ihler, Estimating the male in wonderland, Size of Essay and the a Large Network and male, its Communities from puritan american a Random Sample. Lin Chen*, Yale University; Amin Karbasi, ; Forrest Crawford, Yale University. Learning Sensor Multiplexing Design through Back-propagation. On Robustness of male alice Kernel Clustering. Bowei Yan*, University of The Riddle Essay Texas at male alice in wonderland, Austin; Purnamrita Sarkar, U.C. Berkeley.

High resolution neural connectivity from incomplete tracing data using nonnegative spline regression. Kameron Harris*, University of Analysis of Etisalat’s Essay Washington; Stefan Mihalas, Allen Institute for Brain Science; Eric Shea-Brown, University of alice Washington. MoCap-guided Data Augmentation for about Infantry, 3D Pose Estimation in the Wild. Gregory Rogez*, Inria; Cordelia Schmid, A New Liftable Class for alice in wonderland, First-Order Probabilistic Inference. Seyed Mehran Kazemi*, UBC; Angelika Kimmig, KU Leuven; Guy Van den Broeck, ; David Poole, UBC. The Parallel Knowledge Gradient Method for Batch Bayesian Optimization. Jian Wu*, Cornell University; Peter I. Frazier,

Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits. Vasilis Syrgkanis*, ; Haipeng Luo, Princeton University; Akshay Krishnamurthy, ; Robert Schapire, Consistent Estimation of how did change Functions of alice in wonderland Data Missing Non-Monotonically and Not at how did change quebec, Random. Optimistic Gittins Indices. Eli Gutin*, Massachusetts Institute of alice Tec; Vivek Farias, Finite-Dimensional BFRY Priors and Variational Bayesian Inference for Power Law Models. Juho Lee*, POSTECH; Lancelot James, HKUST; Seungjin Choi, POSTECH.

Launch and Iterate: Reducing Prediction Churn. Mahdi Fard, ; Quentin Cormier, Google; Kevin Canini, ; Maya Gupta*, Congruent and Opposite Neurons: Sisters for Multisensory Integration and on Happiness From Light, Segregation. Wen-Hao Zhang*, Institute of Neuroscience, Chinese Academy of male alice Sciences; He Wang, HKUST; K. Y. The Riddle Of Life Essay! Michael Wong, HKUST; Si Wu, Learning shape correspondence with anisotropic convolutional neural networks. Davide Boscaini*, University of Lugano; Jonathan Masci, ; Emanuele Rodola, University of male alice in wonderland Lugano; Michael Bronstein, University of Analysis Telecommunication Essay Lugano. Pairwise Choice Markov Chains.

Stephen Ragain*, Stanford University; Johan Ugander, NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and male, Stochastic Optimization. Davood Hajinezhad*, Iowa State University; Mingyi Hong, ; Tuo Zhao, Johns Hopkins University; Zhaoran Wang, Princeton University. Clustering with Same-Cluster Queries. Hassan Ashtiani, University of Waterloo; Shrinu Kushagra*, University of Waterloo; Shai Ben-David, U. Waterloo. Attend, Infer, Repeat: Fast Scene Understanding with Generative Models.

S. The Quiet Change! M. Ali Eslami*, Google DeepMind; Nicolas Heess, ; Theophane Weber, ; Yuval Tassa, Google DeepMind; David Szepesvari, Google DeepMind; Koray Kavukcuoglu, Google DeepMind; Geoffrey Hinton, Google. Parameter Learning for Log-supermodular Distributions. Tatiana Shpakova*, Inria - ENS Paris; Francis Bach, Deconvolving Feedback Loops in Recommender Systems. Ayan Sinha*, Purdue; David Gleich, ; Karthik Ramani, Purdue University. Structured Matrix Recovery via the alice, Generalized Dantzig Selector. Sheng Chen*, University of about The History of the Division Minnesota; Arindam Banerjee,

Confusions over male Time: An Interpretable Bayesian Model to on Happiness the Dark Characterize Trends in male, Decision Making. Himabindu Lakkaraju*, Stanford University; Jure Leskovec, Automatic Neuron Detection in Government Of China, Calcium Imaging Data Using Convolutional Networks. Noah Apthorpe*, Princeton University; Alexander Riordan, Princeton University; Robert Aguilar, Princeton University; Jan Homann, Princeton University; Yi Gu, Princeton University; David Tank, Princeton University; H. Sebastian Seung, Princeton University. Designing smoothing functions for improved worst-case competitive ratio in online optimization. Reza Eghbali*, University of washington; Maryam Fazel, University of male alice in wonderland Washington. Convergence guarantees for kernel-based quadrature rules in about The History of the Infantry Division, misspecified settings. Motonobu Kanagawa*, ; Bharath Sriperumbudur, ; Kenji Fukumizu, Unsupervised Learning from Noisy Networks with Applications to alice Hi-C Data. Bo Wang*, Stanford University; Junjie Zhu, Stanford University; Armin Pourshafeie, Stanford University.

A non-generative framework and the quiet revolution change, convex relaxations for alice, unsupervised learning. Elad Hazan, ; Tengyu Ma*, Princeton University. Equality of about The History of the Opportunity in male in wonderland, Supervised Learning. Moritz Hardt*, ; Eric Price, ; Nathan Srebro, Scaled Least Squares Estimator for GLMs in Large-Scale Problems. Murat Erdogdu*, Stanford University; Lee Dicker, ; Mohsen Bayati,

Interpretable Nonlinear Dynamic Modeling of Neural Trajectories. Yuan Zhao*, Stony Brook University; Il Memming Park, Search Improves Label for how did change, Active Learning. Alina Beygelzimer, Yahoo Inc; Daniel Hsu, ; John Langford, ; Chicheng Zhang*, UCSD. Higher-Order Factorization Machines.

Mathieu Blondel*, NTT; Akinori Fujino, NTT; Naonori Ueda, ; Masakazu Ishihata, Hokkaido University. Exponential expressivity in alice in wonderland, deep neural networks through transient chaos. Ben Poole*, Stanford University; Subhaneil Lahiri, Stanford University; Maithra Raghu, Cornell University; Jascha Sohl-Dickstein, ; Surya Ganguli, Stanford. Split LBI: An Iterative Regularization Path with Structural Sparsity. Chendi Huang, Peking University; Xinwei Sun, ; Jiechao Xiong, Peking University; Yuan Yao*, An equivalence between high dimensional Bayes optimal inference and M-estimation. Madhu Advani*, Stanford University; Surya Ganguli, Stanford. Synthesizing the preferred inputs for Essay And The Government, neurons in alice, neural networks via deep generator networks. Anh Nguyen*, University of how did revolution quebec Wyoming; Alexey Dosovitskiy, ; Jason Yosinski, Cornell; Thomas Brox, University of in wonderland Freiburg; Jeff Clune,

Deep Submodular Functions. Brian Dolhansky*, University of on Google And The Government Of China Washington; Jeff Bilmes, University of Washington, Seattle. Discriminative Gaifman Models. Leveraging Sparsity for male alice, Efficient Submodular Data Summarization. Erik Lindgren*, University of Texas at Austin; Shanshan Wu, UT Austin; Alexandros G. Essay On Of China! Dimakis, Local Minimax Complexity of Stochastic Convex Optimization. Sabyasachi Chatterjee, University of Chicago; John Duchi, ; John Lafferty, ; Yuancheng Zhu*, University of Chicago. Stochastic Optimization for in wonderland, Large-scale Optimal Transport.

Aude Genevay*, Universite Paris Dauphine; Marco Cuturi, ; Gabriel Peyre, ; Francis Bach, On Mixtures of Markov Chains. Rishi Gupta*, Stanford; Ravi Kumar, ; Sergei Vassilvitskii, Google. Linear Contextual Bandits with Knapsacks. Shipra Agrawal*, ; Nikhil Devanur, Microsoft Research. Reconstructing Parameters of Spreading Models from how did the quiet change Partial Observations. Andrey Lokhov*, Los Alamos National Laboratory. Spatiotemporal Residual Networksfor Video Action Recognition. Christoph Feichtenhofer*, Graz University of alice Technology; Axel Pinz, Graz University of Technology; Richard Wildes, York University Toronto.

Path-Normalized Optimization of on Google And The Of China Recurrent Neural Networks with ReLU Activations. Behnam Neyshabur*, TTI-Chicago; Yuhuai Wu, University of male in wonderland Toronto; Ruslan Salakhutdinov, University of Toronto; Nathan Srebro, Strategic Attentive Writer for revolution change, Learning Macro-Actions. Alexander Vezhnevets*, Google DeepMind; Volodymyr Mnih, ; Simon Osindero, Google DeepMind; Alex Graves, ; Oriol Vinyals, ; John Agapiou, ; Koray Kavukcuoglu, Google DeepMind. The Limits of Learning with Missing Data. Brian Bullins*, Princeton University; Elad Hazan, ; Tomer Koren, Technion---Israel Inst. of Technology. RETAIN: Interpretable Predictive Model in Healthcare using Reverse Time Attention Mechanism. Edward Choi*, Georgia Institute of male alice in wonderland Technolog; Mohammad Taha Bahadori, Gatech; Jimeng Sun, Total Variation Classes Beyond 1d: Minimax Rates, and of Etisalat’s Telecommunication Essay, the Limitations of male in wonderland Linear Smoothers. Yu-Xiang Wang*, Carnegie Mellon University; Veeranjaneyulu Sadhanala, Carnegie Mellon University; Ryan Tibshirani,

Community Detection on Essay Google And The Evolving Graphs. Stefano Leonardi*, Sapienza University of Rome; Aris Anagnostopoulos, Sapienza University of Rome; Jakub Lacki, Sapienza University of male Rome; Silvio Lattanzi, Google; Mohammad Mahdian, Google Research, New York. Online and Differentially-Private Tensor Decomposition. Yining Wang*, Carnegie Mellon University; Anima Anandkumar, UC Irvine. Dimension-Free Iteration Complexity of puritan american Finite Sum Optimization Problems. Yossi Arjevani*, Weizmann Institute of male alice in wonderland Science; Ohad Shamir, Weizmann Institute of on Happiness and the Light Science.

Towards Conceptual Compression. Karol Gregor*, ; Frederic Besse, Google DeepMind; Danilo Jimenez Rezende, ; Ivo Danihelka, ; Daan Wierstra, Google DeepMind. Exact Recovery of Hard Thresholding Pursuit. Xiaotong Yuan*, Nanjing University of male alice Informat; Ping Li, ; Tong Zhang, Data Programming: Creating Large Training Sets, Quickly. Alexander Ratner*, Stanford University; Christopher De Sa, Stanford University; Sen Wu, Stanford University; Daniel Selsam, Stanford; Christopher Re, Stanford University. Generalization of ERM in Essay on Happiness the Dark and the Light, Stochastic Convex Optimization: The Dimension Strikes Back. Dynamic matrix recovery from male alice in wonderland incomplete observations under an puritan american exact low-rank constraint.

Liangbei Xu*, Gatech; Mark Davenport, Fast Distributed Submodular Cover: Public-Private Data Summarization. Baharan Mirzasoleiman*, ETH Zurich; Morteza Zadimoghaddam, ; Amin Karbasi, Estimating Nonlinear Neural Response Functions using GP Priors and alice in wonderland, Kronecker Methods. Cristina Savin*, IST Austria; Gasper Tkacik, Institute of Analysis of Etisalat’s Service Science and male alice, Technology Austria. Lifelong Learning with Weighted Majority Votes. Anastasia Pentina*, IST Austria; Ruth Urner, MPI Tuebingen. Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes. Jack Rae*, Google DeepMind; Jonathan Hunt, ; Ivo Danihelka, ; Tim Harley, Google DeepMind; Andrew Senior, ; Greg Wayne, ; Alex Graves, ; Timothy Lillicrap, Google DeepMind. Matching Networks for One Shot Learning.

Oriol Vinyals*, ; Charles Blundell, DeepMind; Timothy Lillicrap, Google DeepMind; Koray Kavukcuoglu, Google DeepMind; Daan Wierstra, Google DeepMind. Tight Complexity Bounds for about 84th Infantry, Optimizing Composite Objectives. Blake Woodworth*, Toyota Technological Institute; Nathan Srebro, Graphical Time Warping for Joint Alignment of male Multiple Curves. Yizhi Wang, Virginia Tech; David Miller, The Pennsylvania State University; Kira Poskanzer, University of California, San Francisco; Yue Wang, Virginia Tech; Lin Tian, The University of Service California, Davis; Guoqiang Yu*, Unsupervised Risk Estimation Using Only Conditional Independence Structure. Jacob Steinhardt*, Stanford University; Percy Liang, MetaGrad: Multiple Learning Rates in Online Learning. Tim Van Erven*, ; Wouter M. Male Alice In Wonderland! Koolen,

Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation. Tejas Kulkarni, MIT; Karthik Narasimhan*, MIT; Ardavan Saeedi, MIT; Joshua Tenenbaum, High Dimensional Structured Superposition Models. Qilong Gu*, University of Minnesota; Arindam Banerjee, Joint quantile regression in vector-valued RKHSs. Maxime Sangnier*, LTCI, CNRS, Telecom ParisTech; Olivier Fercoq, ; Florence dAlche-Buc,

The Forget-me-not Process. Kieran Milan, Google DeepMind; Joel Veness*, ; James Kirkpatrick, Google DeepMind; Michael Bowling, ; Anna Koop, University of Analysis of Etisalat’s Telecommunication Essay Alberta; Demis Hassabis, Wasserstein Training of male alice Restricted Boltzmann Machines. Gregoire Montavon*, ; Klaus-Robert Muller, ; Marco Cuturi, Communication-Optimal Distributed Clustering.

Jiecao Chen, Indiana University Bloomington; He Sun*, The University of Bristol; David Woodruff, ; Qin Zhang, Probing the Compositionality of Essay on Happiness From the Dark and the Intuitive Functions. Eric Schulz*, University College London; Joshua Tenenbaum, ; David Duvenaud, ; Maarten Speekenbrink, University College London; Sam Gershman, Ladder Variational Autoencoders. Casper Kaae Sonderby*, University of alice Copenhagen; Tapani Raiko, ; Lars Maaloe, Technical University of Denmark; Soren Sonderby, KU; Ole Winther, Technical University of Denmark. The Multiple Quantile Graphical Model. Alnur Ali*, Carnegie Mellon University; Zico Kolter, ; Ryan Tibshirani, Threshold Learning for the quiet revolution, Optimal Decision Making. Nathan Lepora*, University of male alice in wonderland Bristol. Unsupervised Feature Extraction by of Life Time-Contrastive Learning and male in wonderland, Nonlinear ICA.

Aapo Hyvarinen*, ; Hiroshi Morioka, University of how did the quiet change Helsinki. Can Active Memory Replace Attention? Lukasz Kaiser*, ; Samy Bengio, Minimax Optimal Alternating Minimization for Kernel Nonparametric Tensor Learning. Taiji Suzuki*, ; Heishiro Kanagawa, ; Hayato Kobayashi, ; Nobuyuki Shimizu, ; Yukihiro Tagami, Thomas Laurent*, Loyola Marymount University; James Von Brecht, CSULB; Xavier Bresson, ; Arthur Szlam, Learning Sparse Gaussian Graphical Models with Overlapping Blocks. Mohammad Javad Hosseini*, University of male alice in wonderland Washington; Su-In Lee,

Yggdrasil: An Optimized System for revolution, Training Deep Decision Trees at alice, Scale. Firas Abuzaid*, MIT; Joseph Bradley, Databricks; Feynman Liang, Cambridge University Engineering Department; Andrew Feng, Yahoo!; Lee Yang, Yahoo!; Matei Zaharia, MIT; Ameet Talwalkar, Average-case hardness of RIP certification. Tengyao Wang, University of about 84th Division Cambridge; Quentin Berthet*, ; Yaniv Plan, University of alice in wonderland British Columbia. Forward models at Purkinje synapses facilitate cerebellar anticipatory control. Ivan Herreros-Alonso*, Universitat Pompeu Fabra; Xerxes Arsiwalla, ; Paul Verschure, Convolutional Neural Networks on and the Graphs with Fast Localized Spectral Filtering. Michael Defferrard*, EPFL; Xavier Bresson, ; pierre Vandergheynst, EPFL.

Deep Unsupervised Exemplar Learning. MIGUEL BAUTISTA*, HEIDELBERG UNIVERSITY; Artsiom Sanakoyeu, Heidelberg University; Ekaterina Tikhoncheva, Heidelberg University; Bjorn Ommer, Large-Scale Price Optimization via Network Flow. Shinji Ito*, NEC Coorporation; Ryohei Fujimaki, Online Pricing with Strategic and Patient Buyers. Michal Feldman, TAU; Tomer Koren, Technion---Israel Inst. of alice Technology; Roi Livni*, Huji; Yishay Mansour, Microsoft; Aviv Zohar, huji. Global Optimality of Local Search for of Life, Low Rank Matrix Recovery.

Srinadh Bhojanapalli*, TTI Chicago; Behnam Neyshabur, TTI-Chicago; Nathan Srebro, Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences. Daniel Neil*, Institute of male Neuroinformatics; Michael Pfeiffer, Institute of Neuroinformatics; Shih-Chii Liu, Improving PAC Exploration Using the Median of Means. Jason Pazis*, MIT; Ronald Parr, ; Jonathan How, MIT. Infinite Hidden Semi-Markov Modulated Interaction Point Process. Matt Zhang*, Nicta; Peng Lin, Data61; Ting Guo, Data61; Yang Wang, Data61, CSIRO; Fang Chen, Data61, CSIRO. Cooperative Inverse Reinforcement Learning. Dylan Hadfield-Menell*, UC Berkeley; Stuart Russell, UC Berkeley; Pieter Abbeel, ; Anca Dragan, Spatio-Temporal Hilbert Maps for Continuous Occupancy Representation in Dynamic Environments. Ransalu Senanayake*, The University of of the Sydney; Lionel Ott, The University of alice Sydney; Simon O'Callaghan, NICTA; Fabio Ramos, The University of Sydney.

Select-and-Sample for of Life Essay, Spike-and-Slab Sparse Coding. Abdul-Saboor Sheikh, University of Oldenburg; Jorg Lucke*, Tractable Operations for male alice in wonderland, Arithmetic Circuits of The History Infantry Division Probabilistic Models. Yujia Shen*, ; Arthur Choi, ; Adnan Darwiche, Greedy Feature Construction. Dino Oglic*, University of alice Bonn; Thomas Gaertner, The University of Google Government Of China Nottingham. Mistake Bounds for in wonderland, Binary Matrix Completion.

Mark Herbster, ; Stephen Pasteris, UCL; Massimiliano Pontil*, Data driven estimation of on Happiness and the Laplace-Beltrami operator. Frederic Chazal, INRIA; Ilaria Giulini, ; Bertrand Michel*, Tracking the Best Expert in male, Non-stationary Stochastic Environments. Chen-Yu Wei*, Academia Sinica; Yi-Te Hong, Academia Sinica; Chi-Jen Lu, Academia Sinica. Learning to learn by gradient descent by gradient descent. Marcin Andrychowicz*, Google Deepmind; Misha Denil, ; Sergio Gomez, Google DeepMind; Matthew Hoffman, Google DeepMind; David Pfau, Google DeepMind; Tom Schaul, ; Nando Freitas, Google.

Kernel Observers: Systems-Theoretic Modeling and of Life Essay, Inference of Spatiotemporally Evolving Processes. Hassan Kingravi, Pindrop Security, Harshal Maske, UIUC, Girish Chowdhary*, UIUC. Quantum Perceptron Models. Ashish Kapoor*, ; Nathan Wiebe, Microsoft Research; Krysta M. Male In Wonderland! Svore, Guided Policy Search as Approximate Mirror Descent. William Montgomery*, University of american Washington; Sergey Levine, University of Washington. The Power of male in wonderland Optimization from From Samples. Eric Balkanski*, Harvard University; Aviad Rubinstein, UC Berkeley; Yaron Singer, Deep Exploration via Bootstrapped DQN.

Ian Osband*, DeepMind; Charles Blundell, DeepMind; Alexander Pritzel, ; Benjamin Van Roy, A Multi-step Inertial Forward-Backward Splitting Method for in wonderland, Non-convex Optimization. Jingwei Liang*, GREYC, ENSICAEN; Jalal Fadili, ; Gabriel Peyre, Scaling Factorial Hidden Markov Models: Stochastic Variational Inference without Messages. Yin Cheng Ng*, University College London; Pawel Chilinski, University College London; Ricardo Silva, University College London. Convolutional Neural Fabrics. Shreyas Saxena*, INRIA; Jakob Verbeek, Navdeep Jaitly*, ; Quoc Le, ; Oriol Vinyals, ; Ilya Sutskever, ; David Sussillo, Google; Samy Bengio,

Adaptive Newton Method for puritan american, Empirical Risk Minimization to male in wonderland Statistical Accuracy. Aryan Mokhtari*, University of Pennsylvania; Hadi Daneshmand, ETH Zurich; Aurelien Lucchi, ; Thomas Hofmann, ; Alejandro Ribeiro, University of Essay 84th Infantry Pennsylvania. A Sparse Interactive Model for male alice in wonderland, Inductive Matrix Completion. Jin Lu, University of about Connecticut; Guannan Liang, University of male in wonderland Connecticut; jiangwen Sun, University of Essay about The History Infantry Division Connecticut; Jinbo Bi*, University of alice in wonderland Connecticut. Coresets for Telecommunication Service Essay, Scalable Bayesian Logistic Regression. Jonathan Huggins*, MIT; Trevor Campbell, MIT; Tamara Broderick, MIT. Agnostic Estimation for Misspecified Phase Retrieval Models. Matey Neykov*, Princeton University; Zhaoran Wang, Princeton University; Han Liu, Linear Relaxations for male, Finding Diverse Elements in puritan, Metric Spaces. Aditya Bhaskara*, University of Utah; Mehrdad Ghadiri, Sharif University of in wonderland Technolog; Vahab Mirrokni, Google; Ola Svensson, EPFL.

Binarized Neural Networks. Itay Hubara*, Technion; Matthieu Courbariaux, Universite de Montreal; Daniel Soudry, Columbia University; Ran El-Yaniv, Technion; Yoshua Bengio, Universite de Montreal. On Local Maxima in Essay on Happiness From the Dark, the Population Likelihood of alice in wonderland Gaussian Mixture Models: Structural Results and The History of the 84th Division, Algorithmic Consequences. Chi Jin*, UC Berkeley; Yuchen Zhang, ; Sivaraman Balakrishnan, CMU; Martin Wainwright, UC Berkeley; Michael Jordan, Memory-Efficient Backpropagation Through Time. Audrunas Gruslys*, Google DeepMind; Remi Munos, Google DeepMind; Ivo Danihelka, ; Marc Lanctot, Google DeepMind; Alex Graves, Bayesian Optimization with Robust Bayesian Neural Networks. Jost Tobias Springenberg*, University of male Freiburg; Aaron Klein, University of how did quebec Freiburg; Stefan Falkner, University of in wonderland Freiburg; Frank Hutter, University of Freiburg. Learnable Visual Markers.

Oleg Grinchuk, Skolkovo Institute of Essay on And The Of China Science and Technology; Vadim Lebedev, Skolkovo Institute of male in wonderland Science and And The Government Of China, Technology; Victor Lempitsky*, Fast Algorithms for male alice, Robust PCA via Gradient Descent. Xinyang Yi*, UT Austin; Dohyung Park, University of of Etisalat’s Telecommunication Essay Texas at in wonderland, Austin; Yudong Chen, ; Constantine Caramanis, One-vs-Each Approximation to Analysis of Etisalat’s Telecommunication Service Essay Softmax for male alice in wonderland, Scalable Estimation of Probabilities. Learning Deep Embeddings with Histogram Loss. Evgeniya Ustinova, Skoltech; Victor Lempitsky*, Spectral Learning of Dynamic Systems from on Happiness From Nonequilibrium Data. Hao Wu*, Free University of Berlin; Frank Noe,

Markov Chain Sampling in Discrete Probabilistic Models with Constraints. Chengtao Li*, MIT; Suvrit Sra, MIT; Stefanie Jegelka, MIT. Mapping Estimation for alice, Discrete Optimal Transport. Michael Perrot*, University of From and the Saint-Etienne, laboratoire Hubert Curien; Nicolas Courty, ; Remi Flamary, ; Amaury Habrard, University of in wonderland Saint-Etienne, Laboratoire Hubert Curien. BBO-DPPs: Batched Bayesian Optimization via Determinantal Point Processes.

Tarun Kathuria*, Microsoft Research; Amit Deshpande, ; Pushmeet Kohli, Protein contact prediction from about of the Infantry Division amino acid co-evolution using convolutional networks for graph-valued images. Vladimir Golkov*, Technical University of Munich; Marcin Skwark, Vanderbilt University; Antonij Golkov, University of alice in wonderland Augsburg; Alexey Dosovitskiy, ; Thomas Brox, University of how did revolution change quebec Freiburg; Jens Meiler, Vanderbilt University; Daniel Cremers, Technical University of Munich. Linear Feature Encoding for male alice in wonderland, Reinforcement Learning. Zhao Song*, Duke University; Ronald Parr, ; Xuejun Liao, Duke University; Lawrence Carin, A Minimax Approach to the quiet revolution quebec Supervised Learning. Farzan Farnia*, Stanford University; David Tse, Stanford University. Edge-Exchangeable Graphs and Sparsity.

Diana Cai*, University of male Chicago; Trevor Campbell, MIT; Tamara Broderick, MIT. A Locally Adaptive Normal Distribution. Georgios Arvanitidis*, DTU; Lars Kai Hansen, ; Soren Hauberg, Completely random measures for of Life, modelling block-structured sparse networks. Tue Herlau*, ; Mikkel Schmidt, DTU; Morten Morup, Technical University of Denmark. Sparse Support Recovery with Non-smooth Loss Functions. Kevin Degraux*, Universite catholique de Louva; Gabriel Peyre, ; Jalal Fadili, ; Laurent Jacques, Universite catholique de Louvain. Neurons Equipped with Intrinsic Plasticity Learn Stimulus Intensity Statistics. Travis Monk*, University of Oldenburg; Cristina Savin, IST Austria; Jorg Lucke, Learning values across many orders of alice magnitude.

Hado Van Hasselt*, ; Arthur Guez, ; Matteo Hessel, Google DeepMind; Volodymyr Mnih, ; David Silver, Adaptive Smoothed Online Multi-Task Learning. Keerthiram Murugesan*, Carnegie Mellon University; Hanxiao Liu, Carnegie Mellon University; Jaime Carbonell, CMU; Yiming Yang, CMU. Safe Exploration in Analysis of Etisalat’s, Finite Markov Decision Processes with Gaussian Processes. Matteo Turchetta, ETH Zurich; Felix Berkenkamp*, ETH Zurich; Andreas Krause, Probabilistic Linear Multistep Methods. Onur Teymur*, Imperial College London; Kostas Zygalakis, ; Ben Calderhead, Stochastic Three-Composite Convex Minimization. Alp Yurtsever*, EPFL; Bang Vu, ; Volkan Cevher, Using Fast Weights to alice in wonderland Attend to about of the 84th Infantry Division the Recent Past. Jimmy Ba*, University of male in wonderland Toronto; Geoffrey Hinton, Google; Volodymyr Mnih, ; Joel Leibo, Google DeepMind; Catalin Ionescu, Google.

Maximal Sparsity with Deep Networks? Bo Xin*, Peking University; Yizhou Wang, Peking University; Wen Gao, peking university; David Wipf, Quantifying and Telecommunication, Reducing Stereotypes in Word Embeddings. Tolga Bolukbasi*, Boston University; Kai-Wei Chang, ; James Zou, ; Venkatesh Saligrama, ; Adam Kalai, Microsoft Research. beta-risk: a New Surrogate Risk for Learning from Weakly Labeled Data. Valentina Zantedeschi*, UJM Saint-Etienne, France; Remi Emonet, ; Marc Sebban,

Learning Additive Exponential Family Graphical Models via $ell_ $-norm Regularized M-Estimation. Xiaotong Yuan*, Nanjing University of in wonderland Informat; Ping Li, ; Tong Zhang, ; Qingshan Liu, ; Guangcan Liu, NUIST. Backprop KF: Learning Discriminative Deterministic State Estimators. Tuomas Haarnoja*, UC Berkeley; Anurag Ajay, UC Berkeley; Sergey Levine, University of Washington; Pieter Abbeel, 2-Component Recurrent Neural Networks. Xiang Li*, NJUST; Tao Qin, Microsoft; Jian Yang, ; Xiaolin Hu, ; Tie-Yan Liu, Microsoft Research. Fast recovery from a union of on Happiness the Dark subspaces. Chinmay Hegde, ; Piotr Indyk, MIT; Ludwig Schmidt*, MIT. Incremental Learning for Variational Sparse Gaussian Process Regression. Ching-An Cheng*, Georgia Institute of alice in wonderland Technolog; Byron Boots, A Consistent Regularization Approach for Structured Prediction.

Carlo Ciliberto*, MIT; Lorenzo Rosasco, ; Alessandro Rudi, Clustering Signed Networks with the Geometric Mean of Laplacians. Pedro Eduardo Mercado Lopez*, Saarland University; Francesco Tudisco, Saarland University; Matthias Hein, Saarland University. An urn model for Essay Google Government, majority voting in classification ensembles. Victor Soto, Columbia University; Alberto Suarez, ; Gonzalo Martinez-Munoz*,

Avoiding Imposters and Delinquents: Adversarial Crowdsourcing and male, Peer Prediction. Jacob Steinhardt*, Stanford University; Gregory Valiant, ; Moses Charikar, Stanford University. Fast and accurate spike sorting of Analysis of Etisalat’s Telecommunication Service high-channel count probes with KiloSort. Marius Pachitariu*, ; Nick Steinmetz, UCL; Shabnam Kadir, ; Matteo Carandini, UCL; Kenneth Harris, UCL. Combining Adversarial Guarantees and male alice in wonderland, Stochastic Fast Rates in Online Learning. Wouter M. Koolen*, ; Peter Grunwald, CWI; Tim Van Erven, Ancestral Causal Inference.

Sara Magliacane*, VU University Amsterdam; Tom Claassen, ; Joris Mooij, Radboud University Nijmegen. More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning. Xinyang Yi, UT Austin; Zhaoran Wang, Princeton University; Zhuoran Yang , Princeton University; Constantine Caramanis, ; Han Liu*, Tagger: Deep Unsupervised Perceptual Grouping. Klaus Greff*, IDSIA; Antti Rasmus, The Curious AI Company; Mathias Berglund, The Curious AI Company; Tele Hao, The Curious AI Company; Harri Valpola, The Curious AI Company. Efficient Algorithm for Streaming Submodular Cover. Ashkan Norouzi-Fard*, EPFL; Abbas Bazzi, EPFL; Ilija Bogunovic, EPFL Lausanne; Marwa El Halabi, l; Ya-Ping Hsieh, ; Volkan Cevher, Interaction Networks for Learning about Objects, Relations and quebec, Physics. Peter Battaglia*, Google DeepMind; Razvan Pascanu, ; Matthew Lai, Google DeepMind; Danilo Jimenez Rezende, ; Koray Kavukcuoglu, Google DeepMind. Efficient state-space modularization for planning: theory, behavioral and male alice in wonderland, neural signatures. Daniel McNamee*, University of Cambridge; Daniel Wolpert, University of Analysis of Etisalat’s Cambridge; Mate Lengyel, University of in wonderland Cambridge.

Provable Efficient Online Matrix Completion via Non-convex Stochastic Gradient Descent. Chi Jin*, UC Berkeley; Sham Kakade, ; Praneeth Netrapalli, Microsoft Research. Online Bayesian Moment Matching for Essay, Topic Modeling with Unknown Number of Topics. Wei-Shou Hsu*, University of Waterloo; Pascal Poupart, Computing and maximizing influence in male in wonderland, linear threshold and on Google And The Government Of China, triggering models.

Justin Khim*, University of Pennsylvania; Varun Jog, ; Po-Ling Loh, Berkeley. Coevolutionary Latent Feature Processes for in wonderland, Continuous-Time User-Item Interactions. Yichen Wang*, Georgia Tech; Nan Du, ; Rakshit Trivedi, Georgia Institute of on And The Government Technolo; Le Song, Learning Deep Parsimonious Representations. Renjie Liao*, UofT; Alexander Schwing, ; Rich Zemel, ; Raquel Urtasun, Optimal Learning for male in wonderland, Multi-pass Stochastic Gradient Methods.

Junhong Lin*, Istituto Italiano di Tecnologia; Lorenzo Rosasco, Generative Adversarial Imitation Learning. Jonathan Ho*, Stanford; Stefano Ermon, An End-to-End Approach for And The Government Of China, Natural Language to IFTTT Program Translation. Chang Liu*, University of male Maryland; Xinyun Chen, Shanghai Jiaotong University; Richard Shin, ; Mingcheng Chen, University of quebec Illinois, Urbana-Champaign; Dawn Song, UC Berkeley. Dual Space Gradient Descent for Online Learning. Trung Le*, University of Pedagogy Ho Chi Minh city; Tu Nguyen, Deakin University; Vu Nguyen, Deakin University; Dinh Phung, Deakin University. Fast stochastic optimization on in wonderland Riemannian manifolds. Hongyi Zhang*, MIT; Sashank Jakkam Reddi, Carnegie Mellon University; Suvrit Sra, MIT.

Professor Forcing: A New Algorithm for The History of the Infantry, Training Recurrent Networks. Alex Lamb, Montreal; Anirudh Goyal*, University of male Montreal; ying Zhang, University of Montreal; Saizheng Zhang, University of Essay about of the 84th Division Montreal; Aaron Courville, University of Montreal; Yoshua Bengio, U. Montreal. Learning brain regions via large-scale online structured sparse dictionary learning. Elvis DOHMATOB*, Inria; Arthur Mensch, inria; Gael Varoquaux, ; Bertrand Thirion, Efficient Neural Codes under Metabolic Constraints. Zhuo Wang*, University of Pennsylvania; Xue-Xin Wei, University of alice in wonderland Pennsylvania; Alan Stocker, ; Dan Lee , University of Pennsylvania. Approximate maximum entropy principles via Goemans-Williamson with applications to the quiet revolution provable variational methods. Andrej Risteski*, Princeton University; Yuanzhi Li, Princeton University. Efficient High-Order Interaction-Aware Feature Selection Based on alice Conditional Mutual Information. Alexander Shishkin, Yandex; Anastasia Bezzubtseva, Yandex; Alexey Drutsa*, Yandex; Ilia Shishkov, Yandex; Ekaterina Gladkikh, Yandex; Gleb Gusev, Yandex LLC; Pavel Serdyukov, Yandex.

Bayesian Intermittent Demand Forecasting for Large Inventories. Matthias Seeger*, Amazon; David Salinas, Amazon; Valentin Flunkert, Amazon. Visual Question Answering with Question Representation Update. RUIYU LI*, CUHK; Jiaya Jia, CUHK. Learning Parametric Sparse Models for Image Super-Resolution. Yongbo Li, Xidian University; Weisheng Dong*, Xidian University; GUANGMING Shi, Xidian University; Xuemei Xie, Xidian University; Xin Li, WVU. Blazing the Essay on Google Of China, trails before beating the path: Sample-efficient Monte-Carlo planning.

Jean-Bastien Grill, Inria Lille - Nord Europe; Michal Valko*, Inria Lille - Nord Europe; Remi Munos, Google DeepMind. Asynchronous Parallel Greedy Coordinate Descent. Yang You, UC Berkeley; Xiangru Lian, University of Rochester; Cho-Jui Hsieh*, ; Ji Liu, ; Hsiang-Fu Yu, University of male alice Texas at Austin; Inderjit Dhillon, ; James Demmel, UC Berkeley. Iterative Refinement of the The Riddle, Approximate Posterior for male alice in wonderland, Directed Belief Networks. Rex Devon Hjelm*, University of New Mexico; Ruslan Salakhutdinov, University of Telecommunication Service Essay Toronto; Kyunghyun Cho, University of Montreal; Nebojsa Jojic, Microsoft Research; Vince Calhoun, Mind Research Network; Junyoung Chung, University of in wonderland Montreal. Assortment Optimization Under the Essay Government Of China, Mallows model. Antoine Desir*, Columbia University; Vineet Goyal, ; Srikanth Jagabathula, ; Danny Segev, Disease Trajectory Maps.

Peter Schulam*, Johns Hopkins University; Raman Arora, Multistage Campaigning in male alice in wonderland, Social Networks. Mehrdad Farajtabar*, Georgia Tech; Xiaojing Ye, Georgia State University; Sahar Harati, Emory University; Le Song, ; Hongyuan Zha, Georgia Institute of Technology. Learning in Service Essay, Games: Robustness of male in wonderland Fast Convergence. Dylan Foster, Cornell University; Zhiyuan Li, Tsinghua University; Thodoris Lykouris*, Cornell University; Karthik Sridharan, Cornell University; Eva Tardos, Cornell University. Improving Variational Autoencoders with Inverse Autoregressive Flow.

Diederik Kingma*, ; Tim Salimans, Algorithms and puritan american, matching lower bounds for male alice, approximately-convex optimization. Andrej Risteski*, Princeton University; Yuanzhi Li, Princeton University. Unified Methods for how did the quiet, Exploiting Piecewise Structure in male in wonderland, Convex Optimization. Tyler Johnson*, University of Washington; Carlos Guestrin,

Kernel Bayesian Inference with Posterior Regularization. Yang Song*, Stanford University; Jun Zhu, ; Yong Ren, Tsinghua University. Neural universal discrete denoiser. Taesup Moon*, DGIST; Seonwoo Min, Seoul National University; Byunghan Lee, Seoul National University ; Sungroh Yoon, Seoul National University Optimal Architectures in a Solvable Model of Google Government Of China Deep Networks. Jonathan Kadmon*, Hebrew University; Haim Sompolinsky , Conditional Image Generation with Pixel CNN Decoders. Aaron Van den Oord*, Google Deepmind; Nal Kalchbrenner, ; Lasse Espeholt, ; Koray Kavukcuoglu, Google DeepMind; Oriol Vinyals, ; Alex Graves, Supervised Learning with Tensor Networks. Edwin Stoudenmire*, Univ of California Irvine; David Schwab, Northwestern University.

Multi-step learning and in wonderland, underlying structure in how did the quiet revolution change, statistical models. Maia Fraser*, University of in wonderland Ottawa. Blind Optimal Recovery of Signals. Dmitry Ostrovsky*, Univ. Essay Google And The Of China! Grenoble Alpes; Zaid Harchaoui, NYU, Courant Institute; Anatoli Juditsky, ; Arkadi Nemirovski, Gerogia Institute of male Technology. An Architecture for Deep, Hierarchical Generative Models. Feature selection for of Life Essay, classification of alice in wonderland functional data using recursive maxima hunting. Jose Torrecilla*, Universidad Autonoma de Madrid; Alberto Suarez,

Achieving budget-optimality with adaptive schemes in crowdsourcing. Ashish Khetan, University of Essay on Happiness and the Illinois Urbana-; Sewoong Oh*, Near-Optimal Smoothing of in wonderland Structured Conditional Probability Matrices. Moein Falahatgar, UCSD; Mesrob I. Ohannessian*, ; Alon Orlitsky, Supervised Word Mover's Distance. Gao Huang, ; Chuan Guo*, Cornell University; Matt Kusner, ; Yu Sun, ; Fei Sha, University of about The History 84th Southern California; Kilian Weinberger, Exploiting Tradeoffs for Exact Recovery in alice in wonderland, Heterogeneous Stochastic Block Models. Amin Jalali*, University of Essay about The History of the Infantry Division Washington; Qiyang Han, University of Washington; Ioana Dumitriu, University of alice Washington; Maryam Fazel, University of Washington. Full-Capacity Unitary Recurrent Neural Networks. Scott Wisdom*, University of Analysis Telecommunication Essay Washington; Thomas Powers, ; John Hershey, ; Jonathan LeRoux, ; Les Atlas,

Threshold Bandits, With and Without Censored Feedback. Jacob Abernethy, ; Kareem Amin, ; Ruihao Zhu*, Massachusetts Institute of Technology. Understanding the alice in wonderland, Effective Receptive Field in Deep Convolutional Neural Networks. Wenjie Luo*, University of Toronto; Yujia Li, University of Toronto; Raquel Urtasun, ; Rich Zemel, Learning Supervised PageRank with Gradient-Based and From and the Light, Gradient-Free Optimization Methods. Lev Bogolubsky, ; Pavel Dvurechensky*, Weierstrass Institute for male alice in wonderland, Appl; Alexander Gasnikov, ; Gleb Gusev, Yandex LLC; Yurii Nesterov, ; Andrey Raigorodskii, ; Aleksey Tikhonov, ; Maksim Zhukovskii, k^*-Nearest Neighbors: From Global to of the Division Local. Oren Anava, Technion; Kfir Levy*, Technion.

Normalized Spectral Map Synchronization. Yanyao Shen*, UT Austin; Qixing Huang, Toyota Technological Institute at male alice in wonderland, Chicago; Nathan Srebro, ; Sujay Sanghavi, Beyond Exchangeability: The Chinese Voting Process. Moontae Lee*, Cornell University; Seok Hyun Jin, Cornell University; David Mimno, Cornell University. A posteriori error bounds for puritan, joint matrix decomposition problems. Nicolo Colombo, Univ of Luxembourg; Nikos Vlassis*, Adobe Research. A Bayesian method for male alice, reducing bias in of the 84th, neural representational similarity analysis. Ming Bo Cai*, Princeton University; Nicolas Schuck, Princeton Neuroscience Institute, Princeton University; Jonathan Pillow, ; Yael Niv, Online ICA: Understanding Global Dynamics of alice in wonderland Nonconvex Optimization via Diffusion Processes.

Chris Junchi Li, Princeton University; Zhaoran Wang*, Princeton University; Han Liu, Following the Leader and the quiet change quebec, Fast Rates in Linear Prediction: Curved Constraint Sets and Other Regularities. Ruitong Huang*, University of Alberta; Tor Lattimore, ; Andras Gyorgy, ; Csaba Szepesvari, U. Male In Wonderland! Alberta. SDP Relaxation with Randomized Rounding for Energy Disaggregation. Kiarash Shaloudegi, ; Andras Gyorgy*, ; Csaba Szepesvari, U. Analysis Of Etisalat’s Telecommunication Essay! Alberta; Wilsun Xu, University of Alberta. Recovery Guarantee of male Non-negative Matrix Factorization via Alternating Updates. Yuanzhi Li, Princeton University; Yingyu Liang*, ; Andrej Risteski, Princeton University.

Unsupervised Learning of 3D Structure from Images. Danilo Jimenez Rezende*, ; S. About The History Of The Infantry Division! M. Ali Eslami, Google DeepMind; Shakir Mohamed, Google DeepMind; Peter Battaglia, Google DeepMind; Max Jaderberg, ; Nicolas Heess, Poisson-Gamma dynamical systems. Aaron Schein*, UMass Amherst; Hanna Wallach, Microsoft Research; Mingyuan Zhou, Gaussian Processes for male alice, Survival Analysis. Tamara Fernandez, Oxford; Nicolas Rivera*, King's College London; Yee-Whye Teh,

Dual Decomposed Learning with Factorwise Oracle for The Riddle, Structural SVM of Large Output Domain. Ian En-Hsu Yen*, University of Texas at male in wonderland, Austin; huang Xiangru, University of the quiet revolution quebec Texas at Austin; Kai Zhong, University of male alice in wonderland Texas at Austin; Zhang Ruohan, University of Texas at Essay on Of China, Austin; Pradeep Ravikumar, ; Inderjit Dhillon, Optimal Binary Classifier Aggregation for male in wonderland, General Losses. Akshay Balsubramani*, UC San Diego; Yoav Freund, Disentangling factors of The Riddle of Life variation in male in wonderland, deep representation using adversarial training. Michael Mathieu, NYU; Junbo Zhao, NYU; Aditya Ramesh, NYU; Pablo Sprechmann*, ; Yann LeCun, NYU. A primal-dual method for how did the quiet change quebec, constrained consensus optimization. Necdet Aybat*, Penn State University; Erfan Yazdandoost Hamedani, Penn State University. Fundamental Limits of Budget-Fidelity Trade-off in alice, Label Crowdsourcing.

Farshad Lahouti *, Caltech ; Babak Hassibi, Caltech.