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NIPS · 24.8k rows

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6,600	Reducing Reparameterization Gradient Variance Andrew C. Miller∗ Harvard University acm@seas.harvard.edu Nicholas J. Foti University of Washington nfoti@uw.edu Alexander D’Amour UC Berkeley alexdamour@berkeley.edu Ryan P. Adams Google Brain and Princeton University rpa@princeton.edu Abstract ...	2017	133
6,601	Min-Max Propagation Christopher Srinivasa University of Toronto Borealis AI christopher.srinivasa @gmail.com Inmar Givoni University of Toronto inmar.givoni @gmail.com Siamak Ravanbakhsh University of British Columbia siamakx@cs.ubc.ca Brendan J. Frey University of Toronto Vector Ins...	2017	134
6,602	Statistical Cost Sharing Eric Balkanski Harvard University ericbalkanski@g.harvard.edu Umar Syed Google NYC usyed@google.com Sergei Vassilvitskii Google NYC sergeiv@google.com Abstract We study the cost sharing problem for cooperative games in situations where the cost function C is not availabl...	2017	135
6,603	Dilated Recurrent Neural Networks Shiyu Chang1⇤, Yang Zhang1⇤, Wei Han2⇤, Mo Yu1, Xiaoxiao Guo1, Wei Tan1, Xiaodong Cui1, Michael Witbrock1, Mark Hasegawa-Johnson2, Thomas S. Huang2 1IBM Thomas J. Watson Research Center, Yorktown, NY 10598, USA 2University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA ...	2017	136
6,604	The Expressive Power of Neural Networks: A View from the Width Zhou Lu1,3 1400010739@pku.edu.cn Hongming Pu1 1400010621@pku.edu.cn Feicheng Wang1,3 1400010604@pku.edu.cn Zhiqiang Hu2 huzq@pku.edu.cn Liwei Wang2,3 wanglw@cis.pku.edu.cn 1, Department of Mathematics, Peking University 2, Key Labo...	2017	137
6,605	Inverse Reward Design Dylan Hadﬁeld-Menell Smitha Milli Pieter Abbeel∗ Stuart Russell Anca D. Dragan Department of Electrical Engineering and Computer Science University of California, Berkeley Berkeley, CA 94709 {dhm, smilli, pabbeel, russell, anca}@cs.berkeley.edu Abstract Autonomous agents opti...	2017	138
6,606	The power of absolute discounting: all-dimensional distribution estimation Moein Falahatgar UCSD moein@ucsd.edu Mesrob Ohannessian TTIC mesrob@gmail.com Alon Orlitsky UCSD alon@ucsd.edu Venkatadheeraj Pichapati UCSD dheerajpv7@ucsd.edu Abstract Categorical models are a natural ﬁt for many ...	2017	139
6,607	Model-Powered Conditional Independence Test Rajat Sen1,, Ananda Theertha Suresh2,, Karthikeyan Shanmugam3,*, Alexandros G. Dimakis1, and Sanjay Shakkottai1 1The University of Texas at Austin 2Google, New York 3IBM Research, Thomas J. Watson Center Abstract We consider the problem of non-parametric Condi...	2017	14
6,608	A Uniﬁed Game-Theoretic Approach to Multiagent Reinforcement Learning Marc Lanctot DeepMind lanctot@ Vinicius Zambaldi DeepMind vzambaldi@ Audr¯unas Gruslys DeepMind audrunas@ Angeliki Lazaridou DeepMind angeliki@ Karl Tuyls DeepMind karltuyls@ Julien Pérolat DeepMind perolat@ Da...	2017	140
6,609	Spectral Mixture Kernels for Multi-Output Gaussian Processes Gabriel Parra Department of Mathematical Engineering Universidad de Chile gparra@dim.uchile.cl Felipe Tobar Center for Mathematical Modeling Universidad de Chile ftobar@dim.uchile.cl Abstract Early approaches to multiple-output Gaussian ...	2017	141
6,610	Aﬃne-Invariant Online Optimization and the Low-rank Experts Problem Tomer Koren Google Brain 1600 Amphitheatre Pkwy Mountain View, CA 94043 tkoren@google.com Roi Livni Princeton University 35 Olden St. Princeton, NJ 08540 rlivni@cs.princeton.edu Abstract We present a new aﬃne-invariant optimiz...	2017	142
6,611	Pose Guided Person Image Generation Liqian Ma1 Xu Jia2∗ Qianru Sun3∗ Bernt Schiele3 Tinne Tuytelaars2 Luc Van Gool1,4 1KU-Leuven/PSI, TRACE (Toyota Res in Europe) 2KU-Leuven/PSI, IMEC 3Max Planck Institute for Informatics, Saarland Informatics Campus 4ETH Zurich {liqian.ma, xu.jia, tinne.tuytelaar...	2017	143
6,612	Successor Features for Transfer in Reinforcement Learning André Barreto, Will Dabney, Rémi Munos, Jonathan J. Hunt, Tom Schaul, Hado van Hasselt, David Silver {andrebarreto,wdabney,munos,jjhunt,schaul,hado,davidsilver}@google.com DeepMind Abstract Transfer in reinforcement learning refers to the notion th...	2017	144
6,613	On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning Xingguo Li1,4 Lin F. Yang2⇤ Jason Ge2 Jarvis Haupt1 Tong Zhang3 Tuo Zhao4† 1University of Minnesota 2Princeton University 3Tencent AI Lab 4Georgia Tech Abstract We propose a DC proximal Newton algorithm for s...	2017	145
6,614	Hypothesis Transfer Learning via Transformation Functions Simon S. Du Carnegie Mellon University ssdu@cs.cmu.edu Jayanth Koushik Carnegie Mellon University jayanthkoushik@cmu.edu Aarti Singh Carnegie Mellon University aartisingh@cmu.edu Barnabás Póczos Carnegie Mellon University bapoczos@cs.cm...	2017	146
6,615	Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting Yue Wang ∗ School of Science Beijing Jiaotong University 11271012@bjtu.edu.cn Wei Chen Microsoft Research wche@microsoft.com Yuting Liu School of Science Beijing Jiaotong University ytliu@bjtu.edu.cn Zhi-Ming Ma ...	2017	147
6,616	Variational Inference via χ Upper Bound Minimization Adji B. Dieng Columbia University Dustin Tran Columbia University Rajesh Ranganath Princeton University John Paisley Columbia University David M. Blei Columbia University Abstract Variational inference (VI) is widely used as an efﬁcient alte...	2017	148
6,617	A Probabilistic Framework for Nonlinearities in Stochastic Neural Networks Qinliang Su Xuejun Liao Lawrence Carin Department of Electrical and Computer Engineering Duke University, Durham, NC, USA {qs15, xjliao, lcarin}@duke.edu Abstract We present a probabilistic framework for nonlinearities, based o...	2017	149
6,618	Learning Multiple Tasks with Multilinear Relationship Networks Mingsheng Long, Zhangjie Cao, Jianmin Wang, Philip S. Yu School of Software, Tsinghua University, Beijing 100084, China {mingsheng,jimwang}@tsinghua.edu.cn caozhangjie14@gmail.com psyu@uic.edu Abstract Deep networks trained on large-scale da...	2017	15
6,619	Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation Yuhuai Wu∗ University of Toronto Vector Institute ywu@cs.toronto.edu Elman Mansimov∗ New York University mansimov@cs.nyu.edu Shun Liao University of Toronto Vector Institute sliao3@cs.toronto.edu ...	2017	150
6,620	Optimistic posterior sampling for reinforcement learning: worst-case regret bounds Shipra Agrawal Columbia University sa3305@columbia.edu Randy Jia Columbia University rqj2000@columbia.edu Abstract We present an algorithm based on posterior sampling (aka Thompson sampling) that achieves near-optimal...	2017	151
6,621	Efﬁcient Second-Order Online Kernel Learning with Adaptive Embedding Daniele Calandriello Alessandro Lazaric Michal Valko SequeL team, INRIA Lille - Nord Europe, France {daniele.calandriello, alessandro.lazaric, michal.valko}@inria.fr Abstract Online kernel learning (OKL) is a ﬂexible framework for pred...	2017	152
6,622	Solving Most Systems of Random Quadratic Equations Gang Wang⋆,∗ Georgios B. Giannakis∗ Yousef Saad† Jie Chen⋆ ⋆Key Lab of Intell. Contr. and Decision of Complex Syst., Beijing Inst. of Technology ∗Digital Tech. Center & Dept. of Electrical and Computer Eng., Univ. of Minnesota †Department of Computer Sc...	2017	153
6,623	Online Reinforcement Learning in Stochastic Games Chen-Yu Wei Institute of Information Science Academia Sinica, Taiwan bahh723@iis.sinica.edu.tw Yi-Te Hong Institute of Information Science Academia Sinica, Taiwan ted0504@iis.sinica.edu.tw Chi-Jen Lu Institute of Information Science Academia Sinica...	2017	154
6,624	Independence clustering (without a matrix) Daniil Ryabko INRIA Lillle, 40 avenue de Halley, Villeneuve d’Ascq, France daniil@ryabko.net Abstract The independence clustering problem is considered in the following formulation: given a set S of random variables, it is required to ﬁnd the ﬁnest partitioning ...	2017	155
6,625	Effective Parallelisation for Machine Learning Michael Kamp University of Bonn and Fraunhofer IAIS kamp@cs.uni-bonn.de Mario Boley Max Planck Institute for Informatics and Saarland University mboley@mpi-inf.mpg.de Olana Missura Google Inc. olanam@google.com Thomas G¨artner University of Nottin...	2017	156
6,626	Deep Mean-Shift Priors for Image Restoration Siavash A. Bigdeli University of Bern bigdeli@inf.unibe.ch Meiguang Jin University of Bern jin@inf.unibe.ch Paolo Favaro University of Bern favaro@inf.unibe.ch Matthias Zwicker University of Bern, and University of Maryland, College Park zwicker@cs.um...	2017	157
6,627	On Structured Prediction Theory with Calibrated Convex Surrogate Losses Anton Osokin INRIA/ENS∗, Paris, France HSE†, Moscow, Russia Francis Bach INRIA/ENS∗, Paris, France Simon Lacoste-Julien MILA and DIRO Université de Montréal, Canada Abstract We provide novel theoretical insights on structured ...	2017	158
6,628	Invariance and Stability of Deep Convolutional Representations Alberto Bietti Inria∗ alberto.bietti@inria.fr Julien Mairal Inria∗ julien.mairal@inria.fr Abstract In this paper, we study deep signal representations that are near-invariant to groups of transformations and stable to the action of diffe...	2017	159
6,629	Query Complexity of Clustering with Side Information Arya Mazumdar and Barna Saha College of Information and Computer Sciences University of Massachusetts Amherst Amherst, MA 01003 {arya,barna}@cs.umass.edu Abstract Suppose, we are given a set of n elements to be clustered into k (unknown) clusters, a...	2017	16
6,630	Variational Memory Addressing in Generative Models Jörg Bornschein Andriy Mnih Daniel Zoran Danilo J. Rezende {bornschein, amnih, danielzoran, danilor}@google.com DeepMind, London, UK Abstract Aiming to augment generative models with external memory, we interpret the output of a memory module with s...	2017	160
6,631	Shallow Updates for Deep Reinforcement Learning Nir Levine∗ Dept. of Electrical Engineering The Technion - Israel Institute of Technology Israel, Haifa 3200003 levin.nir1@gmail.com Tom Zahavy∗ Dept. of Electrical Engineering The Technion - Israel Institute of Technology Israel, Haifa 3200003 tomzaha...	2017	161
6,632	Learning with Bandit Feedback in Potential Games Johanne Cohen LRI-CNRS, Université Paris-Sud,Université Paris-Saclay, France johanne.cohen@lri.fr Amélie Héliou LIX, Ecole Polytechnique, CNRS, AMIBio, Inria, Université Paris-Saclay amelie.heliou@polytechnique.edu Panayotis Mertikopoulos Univ. Grenoble A...	2017	162
6,633	A Greedy Approach for Budgeted Maximum Inner Product Search Hsiang-Fu Yu⇤ Amazon Inc. rofuyu@cs.utexas.edu Cho-Jui Hsieh University of California, Davis chohsieh@ucdavis.edu Qi Lei The University of Texas at Austin leiqi@ices.utexas.edu Inderjit S. Dhillon The University of Texas at Austin ind...	2017	163
6,634	Riemannian approach to batch normalization Minhyung Cho Jaehyung Lee Applied Research Korea, Gracenote Inc. mhyung.cho@gmail.com jaehyung.lee@kaist.ac.kr Abstract Batch Normalization (BN) has proven to be an effective algorithm for deep neural network training by normalizing the input to each neuron and...	2017	164
6,635	Adaptive Clustering through Semideﬁnite Programming Martin Royer Laboratoire de Mathématiques d’Orsay, Univ. Paris-Sud, CNRS, Université Paris-Saclay, 91405 Orsay, France martin.royer@math.u-psud.fr Abstract We analyze the clustering problem through a ﬂexible probabilistic model that aims to identify ...	2017	165
6,636	#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning Haoran Tang1∗, Rein Houthooft34∗, Davis Foote2, Adam Stooke2, Xi Chen2†, Yan Duan2†, John Schulman4, Filip De Turck3, Pieter Abbeel 2† 1 UC Berkeley, Department of Mathematics 2 UC Berkeley, Department of Electrical Engineering a...	2017	166
6,637	Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition Naoya Takeishi§, Yoshinobu Kawahara†,‡, Takehisa Yairi§ §Department of Aeronautics and Astronautics, The University of Tokyo †The Institute of Scientiﬁc and Industrial Research, Osaka University ‡RIKEN Center for Advanced Intelligence Project...	2017	167
6,638	Online Prediction with Selﬁsh Experts Tim Roughgarden Department of Computer Science Stanford University Stanford, CA 94305 tim@cs.stanford.edu Okke Schrijvers Department of Computer Science Stanford University Stanford, CA 94305 okkes@cs.stanford.edu Abstract We consider the problem of binary p...	2017	168
6,639	Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach Slobodan Mitrovi´c∗ EPFL Ilija Bogunovic† EPFL Ashkan Norouzi-Fard‡ EPFL Jakub Tarnawski§ EPFL Volkan Cevher¶ EPFL Abstract We study the classical problem of maximizing a monotone submodular function subject to a c...	2017	169
6,640	Non-parametric Structured Output Networks Andreas M. Lehrmann Disney Research Pittsburgh, PA 15213 andreas.lehrmann@disneyresearch.com Leonid Sigal Disney Research Pittsburgh, PA 15213 lsigal@disneyresearch.com Abstract Deep neural networks (DNNs) and probabilistic graphical models (PGMs) are the ...	2017	17
6,641	Neural Program Meta-Induction Jacob Devlin∗ Google jacobdevlin@google.com Rudy Bunel∗ University of Oxford rudy@robots.ox.ac.uk Rishabh Singh Microsoft Research risin@microsoft.com Matthew Hausknecht Microsoft Research mahauskn@microsoft.com Pushmeet Kohli∗ DeepMind pushmeet@google.com A...	2017	170
6,642	The Scaling Limit of High-Dimensional Online Independent Component Analysis Chuang Wang and Yue M. Lu John A. Paulson School of Engineering and Applied Sciences Harvard University 33 Oxford Street, Cambridge, MA 02138, USA {chuangwang,yuelu}@seas.harvard.edu Abstract We analyze the dynamics of an online...	2017	171
6,643	Practical Locally Private Heavy Hitters Raef Bassily∗ Kobbi Nissim† Uri Stemmer‡ Abhradeep Thakurta§ Abstract We present new practical local differentially private heavy hitters algorithms achieving optimal or near-optimal worst-case error – TreeHist and Bitstogram. In both algorithms, server running ti...	2017	172
6,644	Mixture-Rank Matrix Approximation for Collaborative Filtering Dongsheng Li1 Chao Chen1 Wei Liu2∗ Tun Lu3,4 Ning Gu3,4 Stephen M. Chu1 1IBM Research - China 2Tencent AI Lab, China 3School of Computer Science, Fudan University, China 4Shanghai Key Laboratory of Data Science, Fudan University, China ...	2017	173
6,645	Higher-Order Total Variation Classes on Grids: Minimax Theory and Trend Filtering Methods Veeranjaneyulu Sadhanala Carnegie Mellon University Pittsburgh, PA 15213 vsadhana@cs.cmu.edu Yu-Xiang Wang Carnegie Mellon University/Amazon AI Pittsburgh, PA 15213/Palo Alto, CA 94303 yuxiangw@amazon.com James...	2017	174
6,646	Robust Conditional Probabilities Yoav Wald School of Computer Science and Engineering Hebrew University yoav.wald@mail.huji.ac.il Amir Globerson The Balvatnik School of Computer Science Tel-Aviv University gamir@mail.tau.ac.il Abstract Conditional probabilities are a core concept in machine learning...	2017	175
6,647	Attention Is All You Need Ashish Vaswani∗ Google Brain avaswani@google.com Noam Shazeer∗ Google Brain noam@google.com Niki Parmar∗ Google Research nikip@google.com Jakob Uszkoreit∗ Google Research usz@google.com Llion Jones∗ Google Research llion@google.com Aidan N. Gomez∗† University ...	2017	176
6,648	A General Framework for Robust Interactive Learning∗ Ehsan Emamjomeh-Zadeh† David Kempe‡ Abstract We propose a general framework for interactively learning models, such as (binary or non-binary) classiﬁers, orderings/rankings of items, or clusterings of data points. Our framework is based on a generalizat...	2017	177
6,649	Sample and Computationally Efﬁcient Learning Algorithms under S-Concave Distributions Maria-Florina Balcan Machine Learning Department Carnegie Mellon University, USA ninamf@cs.cmu.edu Hongyang Zhang∗ Machine Learning Department Carnegie Mellon University, USA hongyanz@cs.cmu.edu Abstract We provi...	2017	178
6,650	Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee Alireza Aghasi∗ Institute for Insight Georgia State University IBM TJ Watson aaghasi@gsu.edu Afshin Abdi Department of ECE Georgia Tech abdi@gatech.edu Nam Nguyen IBM TJ Watson nnguyen@us.ibm.com Justin Romberg Dep...	2017	179
6,651	Robust Imitation of Diverse Behaviors Ziyu Wang⇤, Josh Merel⇤, Scott Reed, Greg Wayne, Nando de Freitas, Nicolas Heess DeepMind ziyu,jsmerel,reedscot,gregwayne,nandodefreitas,heess@google.com Abstract Deep generative models have recently shown great promise in imitation learning for motor control. Given eno...	2017	18
6,652	ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games Yuandong Tian1 Qucheng Gong1 Wenling Shang2 Yuxin Wu1 C. Lawrence Zitnick1 1Facebook AI Research 2Oculus 1{yuandong, qucheng, yuxinwu, zitnick}@fb.com 2wendy.shang@oculus.com Abstract In this paper, we pro...	2017	180
6,653	Task-based End-to-end Model Learning in Stochastic Optimization Priya L. Donti Dept. of Computer Science Dept. of Engr. & Public Policy Carnegie Mellon University Pittsburgh, PA 15213 pdonti@cs.cmu.edu Brandon Amos Dept. of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 bamos@c...	2017	181
6,654	Fader Networks: Manipulating Images by Sliding Attributes Guillaume Lample1,2, Neil Zeghidour1,3, Nicolas Usunier1, Antoine Bordes1, Ludovic Denoyer2, Marc’Aurelio Ranzato1 {gl,neilz,usunier,abordes,ranzato}@fb.com ludovic.denoyer@lip6.fr Abstract This paper introduces a new encoder-decoder architecture t...	2017	182
6,655	VAE Learning via Stein Variational Gradient Descent Yunchen Pu, Zhe Gan, Ricardo Henao, Chunyuan Li, Shaobo Han, Lawrence Carin Department of Electrical and Computer Engineering, Duke University {yp42, zg27, r.henao, cl319, shaobo.han, lcarin}@duke.edu Abstract A new method for learning variational autoencode...	2017	183
6,656	Approximation and Convergence Properties of Generative Adversarial Learning Shuang Liu University of California, San Diego shuangliu@ucsd.edu Olivier Bousquet Google Brain obousquet@google.com Kamalika Chaudhuri University of California, San Diego kamalika@cs.ucsd.edu Abstract Generative adversa...	2017	184
6,657	VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning Akash Srivastava School of Informatics University of Edinburgh akash.srivastava@ed.ac.uk Lazar Valkov School of Informatics University of Edinburgh L.Valkov@sms.ed.ac.uk Chris Russell The Alan Turing Institute London cr...	2017	185
6,658	Local Aggregative Games Vikas K. Garg CSAIL, MIT vgarg@csail.mit.edu Tommi Jaakkola CSAIL, MIT tommi@csail.mit.edu Aggregative games provide a rich abstraction to model strategic multi-agent interactions. We introduce local aggregative games, where the payoff of each player is a function of its own acti...	2017	186
6,659	An Error Detection and Correction Framework for Connectomics Jonathan Zung Princeton University jzung@princeton.edu Ignacio Tartavull Princeton University tartavull@princeton.edu Kisuk Lee Princeton University and MIT kisuklee@mit.edu H. Sebastian Seung Princeton University sseung@princeton.ed...	2017	187
6,660	Hindsight Experience Replay Marcin Andrychowicz⇤, Filip Wolski, Alex Ray, Jonas Schneider, Rachel Fong, Peter Welinder, Bob McGrew, Josh Tobin, Pieter Abbeel†, Wojciech Zaremba† OpenAI Abstract Dealing with sparse rewards is one of the biggest challenges in Reinforcement Learning (RL). We present a novel te...	2017	188
6,661	Fixed-Rank Approximation of a Positive-Semideﬁnite Matrix from Streaming Data Joel A. Tropp Caltech jtropp@caltech.edu Alp Yurtsever EPFL alp.yurtsever@epfl.ch Madeleine Udell Cornell mru8@cornell.edu Volkan Cevher EPFL volkan.cevher@epfl.ch Abstract Several important applications, such as...	2017	189
6,662	High-Order Attention Models for Visual Question Answering Idan Schwartz Department of Computer Science Technion idansc@cs.technion.ac.il Alexander G. Schwing Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign aschwing@illinois.edu Tamir Hazan Department of...	2017	19
6,663	The Numerics of GANs Lars Mescheder Autonomous Vision Group MPI Tübingen lars.mescheder@tuebingen.mpg.de Sebastian Nowozin Machine Intelligence and Perception Group Microsoft Research sebastian.nowozin@microsoft.com Andreas Geiger Autonomous Vision Group MPI Tübingen andreas.geiger@tuebingen.mpg...	2017	190
6,664	Cortical microcircuits as gated-recurrent neural networks Rui Ponte Costa∗ Centre for Neural Circuits and Behaviour Dept. of Physiology, Anatomy and Genetics University of Oxford, Oxford, UK rui.costa@cncb.ox.ac.uk Yannis M. Assael∗ Dept. of Computer Science University of Oxford, Oxford, UK and Deep...	2017	191
6,665	Deep Lattice Networks and Partial Monotonic Functions Seungil You, David Ding, Kevin Canini, Jan Pfeifer, Maya R. Gupta Google Research 1600 Amphitheatre Parkway, Mountain View, CA 94043 {siyou,dwding,canini,janpf,mayagupta}@google.com Abstract We propose learning deep models that are monotonic with respe...	2017	192
6,666	Zap Q-Learning Adithya M. Devraj Sean P. Meyn Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32608. adithyamdevraj@ufl.edu, meyn@ece.ufl.edu Abstract The Zap Q-learning algorithm introduced in this paper is an improvement of Watkins’ original algorithm and re...	2017	193
6,667	Contrastive Learning for Image Captioning Bo Dai Dahua Lin Department of Information Engineering, The Chinese University of Hong Kong db014@ie.cuhk.edu.hk dhlin@ie.cuhk.edu.hk Abstract Image captioning, a popular topic in computer vision, has achieved substantial progress in recent years. However, the d...	2017	194
6,668	Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net Anirudh Goyal MILA, Université de Montréal anirudhgoyal9119@gmail.com Nan Rosemary Ke MILA, École Polytechnique de Montréal rosemary.nan.ke@gmail.com Surya Ganguli Stanford University sganguli@stanford.edu Yoshua Be...	2017	195
6,669	Linear Time Computation of Moments in Sum-Product Networks Han Zhao Machine Learning Department Carnegie Mellon University Pittsburgh, PA 15213 han.zhao@cs.cmu.edu Geoff Gordon Machine Learning Department Carnegie Mellon University Pittsburgh, PA 15213 ggordon@cs.cmu.edu Abstract Bayesian onli...	2017	196
6,670	SGD Learns the Conjugate Kernel Class of the Network Amit Daniely Hebrew University and Google Research amit.daniely@mail.huji.ac.il Abstract We show that the standard stochastic gradient decent (SGD) algorithm is guaranteed to learn, in polynomial time, a function that is competitive with the best functi...	2017	197
6,671	Learning to Pivot with Adversarial Networks Gilles Louppe New York University g.louppe@nyu.edu Michael Kagan SLAC National Accelerator Laboratory makagan@slac.stanford.edu Kyle Cranmer New York University kyle.cranmer@nyu.edu Abstract Several techniques for domain adaptation have been proposed to ...	2017	198
6,672	Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration Jason Altschuler MIT jasonalt@mit.edu Jonathan Weed MIT jweed@mit.edu Philippe Rigollet MIT rigollet@mit.edu Abstract Computing optimal transport distances such as the earth mover’s distance is a fundamental...	2017	199
6,673	Joint distribution optimal transportation for domain adaptation Nicolas Courty∗ Université de Bretagne Sud, IRISA, UMR 6074, CNRS, courty@univ-ubs.fr Rémi Flamary∗ Université Côte d’Azur, Lagrange, UMR 7293 , CNRS, OCA remi.flamary@unice.fr Amaury Habrard Univ Lyon, UJM-Saint-Etienne, CNRS, Lab....	2017	2
6,674	FALKON: An Optimal Large Scale Kernel Method Alessandro Rudi ∗ INRIA – Sierra Project-team, ´Ecole Normale Sup´erieure, Paris Luigi Carratino University of Genoa Genova, Italy Lorenzo Rosasco University of Genoa, LCSL, IIT & MIT Abstract Kernel methods provide a principled way to perform non linea...	2017	20
6,675	Universal Style Transfer via Feature Transforms Yijun Li UC Merced yli62@ucmerced.edu Chen Fang Adobe Research cfang@adobe.com Jimei Yang Adobe Research jimyang@adobe.com Zhaowen Wang Adobe Research zhawang@adobe.com Xin Lu Adobe Research xinl@adobe.com Ming-Hsuan Yang UC Merced, NVIDI...	2017	200
6,676	Ensemble Sampling Xiuyuan Lu Stanford University lxy@stanford.edu Benjamin Van Roy Stanford University bvr@stanford.edu Abstract Thompson sampling has emerged as an effective heuristic for a broad range of online decision problems. In its basic form, the algorithm requires computing and sampling fro...	2017	201
6,677	Practical Data-Dependent Metric Compression with Provable Guarantees Piotr Indyk∗ MIT Ilya Razenshteyn∗ MIT Tal Wagner∗ MIT Abstract We introduce a new distance-preserving compact representation of multidimensional point-sets. Given n points in a d-dimensional space where each coordinate is represen...	2017	202
6,678	Partial Hard Thresholding: Towards A Principled Analysis of Support Recovery Jie Shen Department of Computer Science School of Arts and Sciences Rutgers University New Jersey, USA js2007@rutgers.edu Ping Li Department of Statistics and Biostatistics Department of Computer Science Rutgers Universit...	2017	203
6,679	Selective Classiﬁcation for Deep Neural Networks Yonatan Geifman Computer Science Department Technion – Israel Institute of Technology yonatan.g@cs.technion.ac.il Ran El-Yaniv Computer Science Department Technion – Israel Institute of Technology rani@cs.technion.ac.il Abstract Selective classiﬁcatio...	2017	204
6,680	Diverse and Accurate Image Description Using a Variational Auto-Encoder with an Additive Gaussian Encoding Space Liwei Wang Alexander G. Schwing Svetlana Lazebnik {lwang97, aschwing, slazebni}@illinois.edu University of Illinois at Urbana-Champaign Abstract This paper explores image caption generation...	2017	205
6,681	Deconvolutional Paragraph Representation Learning Yizhe Zhang Dinghan Shen Guoyin Wang Zhe Gan Ricardo Henao Lawrence Carin Department of Electrical & Computer Engineering, Duke University Abstract Learning latent representations from long text sequences is an important ﬁrst step in many natural lan...	2017	206
6,682	Learning to See Physics via Visual De-animation Jiajun Wu MIT CSAIL Erika Lu University of Oxford Pushmeet Kohli DeepMind William T. Freeman MIT CSAIL, Google Research Joshua B. Tenenbaum MIT CSAIL Abstract We introduce a paradigm for understanding physical scenes without human annotations. At t...	2017	207
6,683	Adversarial Symmetric Variational Autoencoder Yunchen Pu, Weiyao Wang, Ricardo Henao, Liqun Chen, Zhe Gan, Chunyuan Li and Lawrence Carin Department of Electrical and Computer Engineering, Duke University {yp42, ww109, r.henao, lc267, zg27,cl319, lcarin}@duke.edu Abstract A new form of variational autoencod...	2017	208
6,684	Model evidence from nonequilibrium simulations Michael Habeck Statistical Inverse Problems in Biophysics, Max Planck Institute for Biophysical Chemistry & Institute for Mathematical Stochastics, University of Göttingen, 37077 Göttingen, Germany email mhabeck@gwdg.de Abstract The marginal likelihood, or mode...	2017	209
6,685	Generalized Linear Model Regression under Distance-to-set Penalties Jason Xu University of California, Los Angeles jqxu@ucla.edu Eric C. Chi North Carolina State University eric_chi@ncsu.edu Kenneth Lange University of California, Los Angeles klange@ucla.edu Abstract Estimation in generalized li...	2017	21
6,686	Learning Non-Gaussian Multi-Index Model via Second-Order Stein’s Method Zhuoran Yang⇤ Krishna Balasubramanian⇤ Zhaoran Wang† Han Liu† Abstract We consider estimating the parametric components of semiparametric multi-index models in high dimensions. To bypass the requirements of Gaussianity or elliptical...	2017	210
6,687	Learning spatiotemporal piecewise-geodesic trajectories from longitudinal manifold-valued data Juliette Chevallier CMAP, École polytechnique juliette.chevallier@polytechnique.edu Pr Stéphane Oudard Oncology Department USPC, AP-HP, HEGP Stéphanie Allassonnière CRC, Université Paris Descartes stephani...	2017	211
6,688	SVD-Softmax: Fast Softmax Approximation on Large Vocabulary Neural Networks Kyuhong Shim, Minjae Lee, Iksoo Choi, Yoonho Boo, Wonyong Sung Department of Electrical and Computer Engineering Seoul National University, Seoul, Korea skhu20@snu.ac.kr, {mjlee, ischoi, yhboo}@dsp.snu.ac.kr, wysung@snu.ac.kr Abstra...	2017	212
6,689	Concentration of Multilinear Functions of the Ising Model with Applications to Network Data Constantinos Daskalakis ∗ EECS & CSAIL, MIT costis@csail.mit.edu Nishanth Dikkala∗ EECS & CSAIL, MIT nishanthd@csail.mit.edu Gautam Kamath∗ EECS & CSAIL, MIT g@csail.mit.edu Abstract We prove near-tight c...	2017	213
6,690	Rigorous Dynamics and Consistent Estimation in Arbitrarily Conditioned Linear Systems Alyson K. Fletcher Dept. Statistics UC Los Angeles akfletcher@ucla.edu Mojtaba Sahraee-Ardakan Dept. EE, UC Los Angeles msahraee@ucla.edu Sundeep Rangan Dept. ECE, NYU srangan@nyu.edu Philip Schniter Dept...	2017	214
6,691	OnACID: Online Analysis of Calcium Imaging Data in Real Time Andrea Giovannucci†1 Johannes Friedrich†∗1 Matthew Kaufman‡ Anne K. Churchland‡ Dmitri Chklovskii† Liam Paninski∗ Eftychios A. Pnevmatikakis†2 † Flatiron Institute, New York, NY 10010 ‡ Cold Spring Harbor Laboratory, Cold Spring Harbor, NY...	2017	215
6,692	Action Centered Contextual Bandits Kristjan Greenewald Department of Statistics Harvard University kgreenewald@fas.harvard.edu Ambuj Tewari Department of Statistics University of Michigan tewaria@umich.edu Predrag Klasnja School of Information University of Michigan klasnja@umich.edu Susan Mur...	2017	216
6,693	Cost efﬁcient gradient boosting Sven Peter Heidelberg Collaboratory for Image Processing Interdisciplinary Center for Scientiﬁc Computing University of Heidelberg 69115 Heidelberg, Germany sven.peter@iwr.uni-heidelberg.de Ferran Diego Robert Bosch GmbH Robert-Bosch-Straße 200 31139 Hildesheim, Germa...	2017	217
6,694	Eigenvalue Decay Implies Polynomial-Time Learnability for Neural Networks Surbhi Goel ∗ Department of Computer Science University of Texas at Austin surbhi@cs.utexas.edu Adam Klivans † Department of Computer Science University of Texas at Austin klivans@cs.utexas.edu Abstract We consider the probl...	2017	218
6,695	On Separability of Loss Functions, and Revisiting Discriminative Vs Generative Models Adarsh Prasad Machine Learning Dept. CMU adarshp@andrew.cmu.edu Alexandru Niculescu-Mizil NEC Laboratories America Princeton, NJ, USA alex@nec-labs.com Pradeep Ravikumar Machine Learning Dept. CMU pradeepr@cs...	2017	219
6,696	Fisher GAN Youssef Mroueh⇤, Tom Sercu⇤ mroueh@us.ibm.com, tom.sercu1@ibm.com ⇤Equal Contribution AI Foundations, IBM Research AI IBM T.J Watson Research Center Abstract Generative Adversarial Networks (GANs) are powerful models for learning complex distributions. Stable training of GANs has been addressed...	2017	22
6,697	ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events Evan Racah1,2, Christopher Beckham1,3, Tegan Maharaj1,3, Samira Ebrahimi Kahou4, Prabhat2, Christopher Pal1,3 1 MILA, Université de Montréal, evan.racah@umontreal.ca. 2 Lawr...	2017	220
6,698	A Meta-Learning Perspective on Cold-Start Recommendations for Items Manasi Vartak∗ Massachusetts Institute of Technology mvartak@csail.mit.edu Arvind Thiagarajan Twitter Inc. arvindt@twitter.com Conrado Miranda Twitter Inc. cmiranda@twitter.com Jeshua Bratman Twitter Inc. jbratman@twitter.com ...	2017	221
6,699	Learning Unknown Markov Decision Processes: A Thompson Sampling Approach Yi Ouyang University of California, Berkeley ouyangyi@berkeley.edu Mukul Gagrani University of Southern California mgagrani@usc.edu Ashutosh Nayyar University of Southern California ashutosn@usc.edu Rahul Jain University of...	2017	222

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