Split (1)

NIPS · 24.8k rows

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6,500	Learning to learn by gradient descent by gradient descent Marcin Andrychowicz1, Misha Denil1, Sergio Gómez Colmenarejo1, Matthew W. Hoffman1, David Pfau1, Tom Schaul1, Brendan Shillingford1,2, Nando de Freitas1,2,3 1Google DeepMind 2University of Oxford 3Canadian Institute for Advanced Research marcin.and...	2016	556
6,501	Mixed vine copulas as joint models of spike counts and local ﬁeld potentials Arno Onken Istituto Italiano di Tecnologia 38068 Rovereto (TN), Italy arno.onken@iit.it Stefano Panzeri Istituto Italiano di Tecnologia 38068 Rovereto (TN), Italy stefano.panzeri@iit.it Abstract Concurrent measurements of...	2016	557
6,502	Can Active Memory Replace Attention? Łukasz Kaiser Google Brain lukaszkaiser@google.com Samy Bengio Google Brain bengio@google.com Abstract Several mechanisms to focus attention of a neural network on selected parts of its input or memory have been used successfully in deep learning models in recent ...	2016	558
6,503	Fast Active Set Methods for Online Spike Inference from Calcium Imaging Johannes Friedrich1,2, Liam Paninski1 1Grossman Center and Department of Statistics, Columbia University, New York, NY 2Janelia Research Campus, Ashburn, VA j.friedrich@columbia.edu, liam@stat.columbia.edu Abstract Fluorescent calcium...	2016	559
6,504	Efﬁcient Second Order Online Learning by Sketching Haipeng Luo Princeton University, Princeton, NJ USA haipengl@cs.princeton.edu Alekh Agarwal Microsoft Research, New York, NY USA alekha@microsoft.com Nicolò Cesa-Bianchi Università degli Studi di Milano, Italy nicolo.cesa-bianchi@unimi.it John Langf...	2016	56
6,505	Human Decision-Making under Limited Time Pedro A. Ortega Department of Psychology University of Pennsylvania Philadelphia, PA 19104 ope@seas.upenn.edu Alan A. Stocker Department of Psychology University of Pennsylvania Philadelphia, PA 19014 astocker@sas.upenn.edu Abstract Subjective expected ut...	2016	560
6,506	End-to-End Kernel Learning with Supervised Convolutional Kernel Networks Julien Mairal Inria∗ julien.mairal@inria.fr Abstract In this paper, we introduce a new image representation based on a multilayer kernel machine. Unlike traditional kernel methods where data representation is decoupled from the pre...	2016	561
6,507	Dueling Bandits: Beyond Condorcet Winners to General Tournament Solutions Siddartha Ramamohan Indian Institute of Science Bangalore 560012, India siddartha.yr@csa.iisc.ernet.in Arun Rajkumar Xerox Research Bangalore 560103, India arun_r@csa.iisc.ernet.in Shivani Agarwal University of Pennsylvania ...	2016	562
6,508	Visual Question Answering with Question Representation Update (QRU) Ruiyu Li Jiaya Jia The Chinese University of Hong Kong {ryli,leojia}@cse.cuhk.edu.hk Abstract Our method aims at reasoning over natural language questions and visual images. Given a natural language question about an image, our model up...	2016	563
6,509	Optimal Learning for Multi-pass Stochastic Gradient Methods Junhong Lin LCSL, IIT-MIT, USA junhong.lin@iit.it Lorenzo Rosasco DIBRIS, Univ. Genova, ITALY LCSL, IIT-MIT, USA lrosasco@mit.edu Abstract We analyze the learning properties of the stochastic gradient method when multiple passes over the ...	2016	564
6,510	General Tensor Spectral Co-clustering for Higher-Order Data Tao Wu Purdue University wu577@purdue.edu Austin R. Benson Stanford University arbenson@stanford.edu David F. Gleich Purdue University dgleich@purdue.edu Abstract Spectral clustering and co-clustering are well-known techniques in data a...	2016	565
6,511	Balancing Suspense and Surprise: Timely Decision Making with Endogenous Information Acquisition Ahmed M. Alaa Electrical Engineering Department University of California, Los Angeles Mihaela van der Schaar Electrical Engineering Department University of California, Los Angeles Abstract We develop a Bay...	2016	566
6,512	Generating Long-term Trajectories Using Deep Hierarchical Networks Stephan Zheng Caltech stzheng@caltech.edu Yisong Yue Caltech yyue@caltech.edu Patrick Lucey STATS plucey@stats.com Abstract We study the problem of modeling spatiotemporal trajectories over long time horizons using expert demon...	2016	567
6,513	Natural-Parameter Networks: A Class of Probabilistic Neural Networks Hao Wang, Xingjian Shi, Dit-Yan Yeung Hong Kong University of Science and Technology {hwangaz,xshiab,dyyeung}@cse.ust.hk Abstract Neural networks (NN) have achieved state-of-the-art performance in various applications. Unfortunately in app...	2016	568
6,514	Minimizing Quadratic Functions in Constant Time Kohei Hayashi National Institute of Advanced Industrial Science and Technology hayashi.kohei@gmail.com Yuichi Yoshida National Institute of Informatics and Preferred Infrastructure, Inc. yyoshida@nii.ac.jp Abstract A sampling-based optimization method for ...	2016	569
6,515	Professor Forcing: A New Algorithm for Training Recurrent Networks Anirudh Goyal∗, Alex Lamb∗, Ying Zhang, Saizheng Zhang, Aaron Courville and Yoshua Bengio1 MILA, Université de Montréal, 1CIFAR {anirudhgoyal9119, alex6200, ying.zhlisa, saizhenglisa, aaron.courville, yoshua.umontreal}@gmail.com Abstract ...	2016	57
6,516	Deep ADMM-Net for Compressive Sensing MRI Yan Yang Xi’an Jiaotong University yangyan92@stu.xjtu.edu.cn Jian Sun Xi’an Jiaotong University jiansun@mail.xjtu.edu.cn Huibin Li Xi’an Jiaotong University huibinli@mail.xjtu.edu.cn Zongben Xu Xi’an Jiaotong University zbxu@mail.xjtu.edu.cn Abstract ...	2016	58
6,517	Adaptive Averaging in Accelerated Descent Dynamics Walid Krichene ∗ UC Berkeley walid@eecs.berkeley.edu Alexandre M. Bayen UC Berkeley bayen@berkeley.edu Peter L. Bartlett UC Berkeley and QUT bartlett@cs.berkeley.edu Abstract We study accelerated descent dynamics for constrained convex optimizatio...	2016	59
6,518	Collaborative Recurrent Autoencoder: Recommend while Learning to Fill in the Blanks Hao Wang, Xingjian Shi, Dit-Yan Yeung Hong Kong University of Science and Technology {hwangaz,xshiab,dyyeung}@cse.ust.hk Abstract Hybrid methods that utilize both content and rating information are commonly used in many re...	2016	6
6,519	Dynamic Mode Decomposition with Reproducing Kernels for Koopman Spectral Analysis Yoshinobu Kawaharaab a The Institute of Scientiﬁc and Industrial Research, Osaka University b Center for Advanced Integrated Intelligence Research, RIKEN ykawahara@sanken.osaka-u.ac.jp Abstract A spectral analysis of the Koo...	2016	60
6,520	Total Variation Classes Beyond 1d: Minimax Rates, and the Limitations of Linear Smoothers Veeranjaneyulu Sadhanala Machine Learning Department Carnegie Mellon University Pittsburgh, PA 15213 vsadhana@cs.cmu.edu Yu-Xiang Wang Machine Learning Department Carnegie Mellon University Pittsburgh, PA 15213...	2016	61
6,521	Hardness of Online Sleeping Combinatorial Optimization Problems Satyen Kale∗† Yahoo Research satyen@satyenkale.com Chansoo Lee† Univ. of Michigan, Ann Arbor chansool@umich.edu D´avid P´al Yahoo Research dpal@yahoo-inc.com Abstract We show that several online combinatorial optimization problems t...	2016	62
6,522	Density Estimation via Discrepancy Based Adaptive Sequential Partition Dangna Li ICME, Stanford University Stanford, CA 94305 dangna@stanford.edu Kun Yang Google Mountain View, CA 94043 kunyang@stanford.edu Wing Hung Wong Department of Statistics Stanford University Stanford, CA 94305 whwo...	2016	63
6,523	Quantized Random Projections and Non-Linear Estimation of Cosine Similarity Ping Li Rutgers University pingli@stat.rutgers.edu Michael Mitzenmacher Harvard University michaelm@eecs.harvard.edu Martin Slawski Rutgers University martin.slawski@rutgers.edu Abstract Random projections constitute a s...	2016	64
6,524	Algorithms and matching lower bounds for approximately-convex optimization Yuanzhi Li Department of Computer Science Princeton University Princeton, NJ, 08450 yuanzhil@cs.princeton.edu Andrej Risteski Department of Computer Science Princeton University Princeton, NJ, 08450 risteski@cs.princeton.ed...	2016	65
6,525	The Parallel Knowledge Gradient Method for Batch Bayesian Optimization Jian Wu, Peter I. Frazier Cornell University Ithaca, NY, 14853 {jw926, pf98}@cornell.edu Abstract In many applications of black-box optimization, one can evaluate multiple points simultaneously, e.g. when evaluating the performances ...	2016	66
6,526	Edge-exchangeable graphs and sparsity Diana Cai Dept. of Statistics, U. Chicago Chicago, IL 60637 dcai@uchicago.edu Trevor Campbell CSAIL, MIT Cambridge, MA 02139 tdjc@mit.edu Tamara Broderick CSAIL, MIT Cambridge, MA 02139 tbroderick@csail.mit.edu Abstract Many popular network models rely o...	2016	67
6,527	Stochastic Variance Reduction Methods for Saddle-Point Problems P. Balamurugan INRIA - Ecole Normale Supérieure, Paris balamurugan.palaniappan@inria.fr Francis Bach INRIA - Ecole Normale Supérieure, Paris francis.bach@ens.fr Abstract We consider convex-concave saddle-point problems where the objective...	2016	68
6,528	A Probabilistic Model of Social Decision Making based on Reward Maximization Koosha Khalvati Department of Computer Science University of Washington Seattle, WA 98105 koosha@cs.washington.edu Seongmin A. Park CNRS UMR 5229 Institut des Sciences Cognitives Marc Jeannerod Lyon, France park@isc.cnrs....	2016	69
6,529	Bayesian Intermittent Demand Forecasting for Large Inventories Matthias Seeger, David Salinas, Valentin Flunkert Amazon Development Center Germany Krausenstrasse 38 10115 Berlin matthis@amazon.de, dsalina@amazon.de, flunkert@amazon.de Abstract We present a scalable and robust Bayesian method for demand ...	2016	7
6,530	Bootstrap Model Aggregation for Distributed Statistical Learning Jun Han Department of Computer Science Dartmouth College jun.han.gr@dartmouth.edu Qiang Liu Department of Computer Science Dartmouth College qiang.liu@dartmouth.edu Abstract In distributed, or privacy-preserving learning, we are ofte...	2016	70
6,531	Unsupervised Learning of 3D Structure from Images Danilo Jimenez Rezende* danilor@google.com S. M. Ali Eslami* aeslami@google.com Shakir Mohamed* shakir@google.com Peter Battaglia* peterbattaglia@google.com Max Jaderberg* jaderberg@google.com Nicolas Heess* heess@google.com * Google DeepMind ...	2016	71
6,532	β-risk: a New Surrogate Risk for Learning from Weakly Labeled Data Valentina Zantedeschi∗ Rémi Emonet Marc Sebban ﬁrstname.lastname@univ-st-etienne.fr Univ Lyon, UJM-Saint-Etienne, CNRS, Institut d Optique Graduate School, Laboratoire Hubert Curien UMR 5516, F-42023, SAINT-ETIENNE, France Abstract Dur...	2016	72
6,533	Learning Supervised PageRank with Gradient-Based and Gradient-Free Optimization Methods Lev Bogolubsky1,2, Gleb Gusev1,5, Andrei Raigorodskii5,2,1,8, Aleksey Tikhonov1, Maksim Zhukovskii1,5 Yandex1, Moscow State University2, Buryat State University8 {bogolubsky, gleb57, raigorodsky, altsoph, zhukmax}@yandex-tea...	2016	73
6,534	Globally Optimal Training of Generalized Polynomial Neural Networks with Nonlinear Spectral Methods A. Gautier, Q. Nguyen and M. Hein Department of Mathematics and Computer Science Saarland Informatics Campus, Saarland University, Germany Abstract The optimization problem behind neural networks is highly ...	2016	74
6,535	Optimal Black-Box Reductions Between Optimization Objectives∗ Zeyuan Allen-Zhu zeyuan@csail.mit.edu Institute for Advanced Study & Princeton University Elad Hazan ehazan@cs.princeton.edu Princeton University Abstract The diverse world of machine learning applications has given rise to a plethora o...	2016	75
6,536	Sequential Neural Models with Stochastic Layers Marco Fraccaro† Søren Kaae Sønderby‡ Ulrich Paquet* Ole Winther†‡ † Technical University of Denmark ‡ University of Copenhagen * Google DeepMind Abstract How can we efﬁciently propagate uncertainty in a latent state representation with recurrent neural...	2016	76
6,537	Iterative Reﬁnement of the Approximate Posterior for Directed Belief Networks R Devon Hjelm University of New Mexico and the Mind Research Network dhjelm@mrn.org Kyunghyun Cho Courant Institute & Center for Data Science, New York University kyunghyun.cho@nyu.edu Junyoung Chung University of Montreal ...	2016	77
6,538	Stochastic Multiple Choice Learning for Training Diverse Deep Ensembles Stefan Lee Virginia Tech steﬂee@vt.edu Senthil Purushwalkam Carnegie Mellon University spurushw@andrew.cmu.edu Michael Cogswell Virginia Tech cogswell@vt.edu Viresh Ranjan Virginia Tech rviresh@vt.edu David Crandall In...	2016	78
6,539	Learning shape correspondence with anisotropic convolutional neural networks Davide Boscaini1, Jonathan Masci1, Emanuele Rodol`a1, Michael Bronstein1,2,3 1USI Lugano, Switzerland 2Tel Aviv University, Israel 3Intel, Israel name.surname@usi.ch Abstract Convolutional neural networks have achieved extraord...	2016	79
6,540	Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks Tianfan Xue1 Jiajun Wu1 Katherine L. Bouman1 William T. Freeman1,2 1 Massachusetts Institute of Technology 2 Google Research {tfxue, jiajunwu, klbouman, billf}@mit.edu Abstract We study the problem of synthesizi...	2016	8
6,541	Learning Tree Structured Potential Games Vikas K. Garg CSAIL, MIT vgarg@csail.mit.edu Tommi Jaakkola CSAIL, MIT tommi@csail.mit.edu Abstract Many real phenomena, including behaviors, involve strategic interactions that can be learned from data. We focus on learning tree structured potential games wher...	2016	80
6,542	RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism Edward Choi⇤, Mohammad Taha Bahadori⇤, Joshua A. Kulas⇤, Andy Schuetz†, Walter F. Stewart†, Jimeng Sun⇤ ⇤Georgia Institute of Technology † Sutter Health {mp2893,bahadori,jkulas3}@gatech.edu, {schueta1,stewarwf}...	2016	81
6,543	PAC Reinforcement Learning with Rich Observations Akshay Krishnamurthy University of Massachusetts, Amherst Amherst, MA, 01003 akshay@cs.umass.edu Alekh Agarwal Microsoft Research New York, NY 10011 alekha@microsoft.com John Langford Microsoft Research New York, NY 10011 jcl@microsoft.com Abst...	2016	82
6,544	Generative Shape Models: Joint Text Recognition and Segmentation with Very Little Training Data Xinghua Lou, Ken Kansky, Wolfgang Lehrach, CC Laan Vicarious FPC Inc., San Francisco, USA xinghua,ken,wolfgang,cc@vicarious.com Bhaskara Marthi, D. Scott Phoenix, Dileep George Vicarious FPC Inc., San Francisco, ...	2016	83
6,545	Probabilistic Linear Multistep Methods Onur Teymur Department of Mathematics Imperial College London o@teymur.uk Konstantinos Zygalakis School of Mathematics University of Edinburgh k.zygalakis@ed.ac.uk Ben Calderhead Department of Mathematics Imperial College London b.calderhead@imperial.ac.uk ...	2016	84
6,546	Computational and Statistical Tradeoffs in Learning to Rank Ashish Khetan and Sewoong Oh Department of ISE, University of Illinois at Urbana-Champaign Email: {khetan2,swoh}@illinois.edu Abstract For massive and heterogeneous modern data sets, it is of fundamental interest to provide guarantees on the ...	2016	85
6,547	Split LBI: An Iterative Regularization Path with Structural Sparsity Chendi Huang1, Xinwei Sun1, Jiechao Xiong1, Yuan Yao2,1 1Peking University, 2Hong Kong University of Science and Technology {cdhuang, sxwxiaoxiaohehe, xiongjiechao}@pku.edu.cn, yuany@ust.hk Abstract An iterative regularization path with st...	2016	86
6,548	Incremental Variational Sparse Gaussian Process Regression Ching-An Cheng Institute for Robotics and Intelligent Machines Georgia Institute of Technology Atlanta, GA 30332 cacheng@gatech.edu Byron Boots Institute for Robotics and Intelligent Machines Georgia Institute of Technology Atlanta, GA 30332...	2016	87
6,549	Sublinear Time Orthogonal Tensor Decomposition∗ Zhao Song‡ David P. Woodruff† Huan Zhang⋆ ‡Dept. of Computer Science, University of Texas, Austin, USA †IBM Almaden Research Center, San Jose, USA ⋆Dept. of Electrical and Computer Engineering, University of California, Davis, USA zhaos@utexas.edu, dpwoodru@...	2016	88
6,550	Mapping Estimation for Discrete Optimal Transport Micha¨el Perrot Univ Lyon, UJM-Saint-Etienne, CNRS, Lab. Hubert Curien UMR 5516, F-42023 michael.perrot@univ-st-etienne.fr Nicolas Courty Universit´e de Bretagne Sud, IRISA, UMR 6074, CNRS, courty@univ-ubs.fr R´emi Flamary Universit´e Cˆote d’Azur, ...	2016	89
6,551	Achieving Budget-optimality with Adaptive Schemes in Crowdsourcing Ashish Khetan and Sewoong Oh Department of ISE, University of Illinois at Urbana-Champaign Email: {khetan2,swoh}@illinois.edu Abstract Adaptive schemes, where tasks are assigned based on the data collected thus far, are widely used in prac...	2016	9
6,552	Greedy Feature Construction Dino Oglic† ‡ dino.oglic@uni-bonn.de †Institut für Informatik III Universität Bonn, Germany Thomas Gärtner ‡ thomas.gaertner@nottingham.ac.uk ‡School of Computer Science The University of Nottingham, UK Abstract We present an effective method for supervised feature constr...	2016	90
6,553	Dynamic Network Surgery for Efﬁcient DNNs Yiwen Guo∗ Intel Labs China yiwen.guo@intel.com Anbang Yao Intel Labs China anbang.yao@intel.com Yurong Chen Intel Labs China yurong.chen@intel.com Abstract Deep learning has become a ubiquitous technology to improve machine intelligence. However, most o...	2016	91
6,554	Graph Clustering: Block-models and model free results Yali Wan Department of Statistics University of Washington Seattle, WA 98195-4322, USA yaliwan@washington.edu Marina Meil˘a Department of Statistics University of Washington Seattle, WA 98195-4322, USA mmp@stat.washington.edu Abstract Clust...	2016	92
6,555	CMA-ES with Optimal Covariance Update and Storage Complexity Oswin Krause Dept. of Computer Science University of Copenhagen Copenhagen, Denmark oswin.krause@di.ku.dk Dídac R. Arbonès Dept. of Computer Science University of Copenhagen Copenhagen, Denmark didac@di.ku.dk Christian Igel Dept. of ...	2016	93
6,556	Feature selection in functional data classiﬁcation with recursive maxima hunting Jos´e L. Torrecilla Computer Science Department Universidad Aut´onoma de Madrid 28049 Madrid, Spain joseluis.torrecilla@uam.es Alberto Su´arez Computer Science Department Universidad Aut´onoma de Madrid 28049 Madrid, Sp...	2016	94
6,557	CYCLADES: Conﬂict-free Asynchronous Machine Learning Xinghao Pan⇤, Maximilian Lam⇤, Stephen Tu⇤, Dimitris Papailiopoulos⇤, Ce Zhang†, Michael I. Jordan⇤‡, Kannan Ramchandran⇤, Chris Re†, Benjamin Recht⇤‡ Abstract We present CYCLADES, a general framework for parallelizing stochastic optimization ...	2016	95
6,558	Proximal Stochastic Methods for Nonsmooth Nonconvex Finite-Sum Optimization Sashank J. Reddi Carnegie Mellon University sjakkamr@cs.cmu.edu Suvrit Sra Massachusetts Institute of Technology suvrit@mit.edu Barnabás Póczos Carnegie Mellon University bapoczos@cs.cmu.edu Alexander J. Smola Carnegie M...	2016	96
6,559	Spectral Learning of Dynamic Systems from Nonequilibrium Data Hao Wu and Frank Noé Department of Mathematics and Computer Science Freie Universität Berlin Arnimallee 6, 14195 Berlin {hao.wu,frank.noe}@fu-berlin.de Abstract Observable operator models (OOMs) and related models are one of the most importan...	2016	97
6,560	Dimension-Free Iteration Complexity of Finite Sum Optimization Problems Yossi Arjevani Weizmann Institute of Science Rehovot 7610001, Israel yossi.arjevani@weizmann.ac.il Ohad Shamir Weizmann Institute of Science Rehovot 7610001, Israel ohad.shamir@weizmann.ac.il Abstract Many canonical machine le...	2016	98
6,561	Hierarchical Object Representation for Open-Ended Object Category Learning and Recognition S.Hamidreza Kasaei, Ana Maria Tomé, Luís Seabra Lopes IEETA - Instituto de Engenharia Electrónica e Telemática de Aveiro University of Aveiro, Averio, 3810-193, Portugal {seyed.hamidreza, ana, lsl}@ua.pt Abstract Mo...	2016	99
6,562	Real Time Image Saliency for Black Box Classiﬁers Piotr Dabkowski pd437@cam.ac.uk University of Cambridge Yarin Gal yarin.gal@eng.cam.ac.uk University of Cambridge and Alan Turing Institute, London Abstract In this work we develop a fast saliency detection method that can be applied to any different...	2017	1
6,563	Accelerated consensus via Min-Sum Splitting Patrick Rebeschini Department of Statistics University of Oxford patrick.rebeschini@stats.ox.ac.uk Sekhar Tatikonda Department of Electrical Engineering Yale University sekhar.tatikonda@yale.edu Abstract We apply the Min-Sum message-passing protocol to sol...	2017	10
6,564	Parallel Streaming Wasserstein Barycenters Matthew Staib MIT CSAIL mstaib@mit.edu Sebastian Claici MIT CSAIL sclaici@mit.edu Justin Solomon MIT CSAIL jsolomon@mit.edu Stefanie Jegelka MIT CSAIL stefje@mit.edu Abstract Efﬁciently aggregating data from different sources is a challenging proble...	2017	100
6,565	Adaptive Accelerated Gradient Converging Method under Hölderian Error Bound Condition Mingrui Liu, Tianbao Yang Department of Computer Science The University of Iowa, Iowa City, IA 52242 mingrui-liu, tianbao-yang@uiowa.edu Abstract Recent studies have shown that proximal gradient (PG) method and accelerat...	2017	101
6,566	What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall University of Cambridge agk34@cam.ac.uk Yarin Gal University of Cambridge yg279@cam.ac.uk Abstract There are two major types of uncertainty one can model. Aleatoric uncertainty captures noise inherent in the ob...	2017	102
6,567	Reconstruct & Crush Network Erinç Merdivan1,2, Mohammad Reza Loghmani3 and Matthieu Geist4 1 AIT Austrian Institute of Technology GmbH, Vienna, Austria 2 LORIA (Univ. Lorraine & CNRS), CentraleSupélec, Univ. Paris-Saclay, 57070 Metz, France 3 Vision4Robotics lab, ACIN, TU Wien, Vienna, Austria 4 Université de...	2017	103
6,568	Permutation-based Causal Inference Algorithms with Interventions Yuhao Wang Laboratory for Information and Decision Systems and Institute for Data, Systems and Society Massachusetts Institute of Technology Cambridge, MA 02139 yuhaow@mit.edu Liam Solus Department of Mathematics KTH Royal Institute of...	2017	104
6,569	Deep Dynamic Poisson Factorization Model Chengyue Gong Department of Information Management Peking University cygong@pku.edu.cn Win-bin Huang Department of Information Management Peking University huangwb@pku.edu.cn Abstract A new model, named as deep dynamic poisson factorization model, is proposed...	2017	105
6,570	Scalable Generalized Linear Bandits: Online Computation and Hashing Kwang-Sung Jun UW-Madison kjun@discovery.wisc.edu Aniruddha Bhargava UW-Madison aniruddha@wisc.edu Robert Nowak UW-Madison rdnowak@wisc.edu Rebecca Willett UW-Madison willett@discovery.wisc.edu Abstract Generalized Linear ...	2017	106
6,571	Experimental Design for Learning Causal Graphs with Latent Variables Murat Kocaoglu⇤ Department of Electrical and Computer Engineering The University of Texas at Austin, USA mkocaoglu@utexas.edu Karthikeyan Shanmugam⇤ IBM Research NY, USA karthikeyan.shanmugam2@ibm.com Elias Bareinboim Department of...	2017	107
6,572	Lower bounds on the robustness to adversarial perturbations Jonathan Peck1,2, Joris Roels2,3, Bart Goossens3, and Yvan Saeys1,2 1Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, 9000, Belgium 2Data Mining and Modeling for Biomedicine, VIB Inﬂammation Research Center, ...	2017	108
6,573	Reliable Decision Support using Counterfactual Models Peter Schulam Department of Computer Science Johns Hopkins University Baltimore, MD 21211 pschulam@cs.jhu.edu Suchi Saria Department of Computer Science Johns Hopkins University Baltimore, MD 21211 ssaria@cs.jhu.edu Abstract Decision-makers...	2017	109
6,574	Saliency-based Sequential Image Attention with Multiset Prediction Sean Welleck New York University wellecks@nyu.edu Jialin Mao New York University jialin.mao@nyu.edu Kyunghyun Cho New York University kyunghyun.cho@nyu.edu Zheng Zhang New York University zz@nyu.edu Abstract Humans process ...	2017	11
6,575	Group Additive Structure Identiﬁcation for Kernel Nonparametric Regression Pan Chao Department of Statistics Purdue University West Lafayette, IN 47906 panchao25@gmail.com Michael Zhu Department of Statistics, Purdue University West Lafayette, IN 47906 Center for Statistical Science Department of ...	2017	110
6,576	A multi-agent reinforcement learning model of common-pool resource appropriation Julien Perolat⇤ DeepMind London, UK perolat@google.com Joel Z. Leibo⇤ DeepMind London, UK jzl@google.com Vinicius Zambaldi DeepMind London, UK vzambaldi@google.com Charles Beattie DeepMind London, UK cbeat...	2017	111
6,577	Decoding with Value Networks for Neural Machine Translation Di He1 di_he@pku.edu.cn Hanqing Lu2 hanqinglu@cmu.edu Yingce Xia3 xiayingc@mail.ustc.edu.cn Tao Qin4 taoqin@microsoft.com Liwei Wang1,5 wanglw@cis.pku.edu.cn Tie-Yan Liu4 tie-yan.liu@microsoft.com 1Key Laboratory of Machine Percepti...	2017	112
6,578	Population Matching Discrepancy and Applications in Deep Learning Jianfei Chen, Chongxuan Li, Yizhong Ru, Jun Zhu∗ Dept. of Comp. Sci. & Tech., TNList Lab, State Key Lab for Intell. Tech. & Sys. Tsinghua University, Beijing, 100084, China {chenjian14,licx14,ruyz13}@mails.tsinghua.edu.cn, dcszj@tsinghua.edu.cn...	2017	113
6,579	Predictive State Recurrent Neural Networks Carlton Downey Carnegie Mellon University Pittsburgh, PA 15213 cmdowney@cs.cmu.edu Ahmed Hefny Carnegie Mellon University Pittsburgh, PA, 15213 ahefny@cs.cmu.edu Boyue Li Carnegie Mellon University Pittsburgh, PA, 15213 boyue@cs.cmu.edu Byron Boots ...	2017	114
6,580	Robust Hypothesis Test for Nonlinear Effect with Gaussian Processes Jeremiah Zhe Liu, Brent Coull Department of Biostatistics Harvard University Cambridge, MA 02138 {zhl112@mail, bcoull@hsph}.harvard.edu Abstract This work constructs a hypothesis test for detecting whether an data-generating function ...	2017	115
6,581	Sharpness, Restart and Acceleration Vincent Roulet INRIA, ENS Paris France vincent.roulet@inria.fr Alexandre d’Aspremont CNRS, ENS Paris France aspremon@ens.fr Abstract The Łojasiewicz inequality shows that sharpness bounds on the minimum of convex optimization problems hold almost generically. Sh...	2017	116
6,582	Dynamic Routing Between Capsules Sara Sabour Nicholas Frosst Geoffrey E. Hinton Google Brain Toronto {sasabour, frosst, geoffhinton}@google.com Abstract A capsule is a group of neurons whose activity vector represents the instantiation parameters of a speciﬁc type of entity such as an object or an obj...	2017	117
6,583	InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations Yunzhu Li MIT liyunzhu@mit.edu Jiaming Song Stanford University tsong@cs.stanford.edu Stefano Ermon Stanford University ermon@cs.stanford.edu Abstract The goal of imitation learning is to mimic expert behavior without access t...	2017	118
6,584	A Regularized Framework for Sparse and Structured Neural Attention Vlad Niculae∗ Cornell University Ithaca, NY vlad@cs.cornell.edu Mathieu Blondel NTT Communication Science Laboratories Kyoto, Japan mathieu@mblondel.org Abstract Modern neural networks are often augmented with an attention mechanis...	2017	119
6,585	Adaptive Bayesian Sampling with Monte Carlo EM Anirban Roychowdhury, Srinivasan Parthasarathy Department of Computer Science and Engineering The Ohio State University roychowdhury.7@osu.edu, srini@cse.ohio-state.edu Abstract We present a novel technique for learning the mass matrices in samplers obtained ...	2017	12
6,586	Style Transfer from Non-Parallel Text by Cross-Alignment Tianxiao Shen1 Tao Lei2 Regina Barzilay1 Tommi Jaakkola1 1MIT CSAIL 2ASAPP Inc. 1{tianxiao, regina, tommi}@csail.mit.edu 2tao@asapp.com Abstract This paper focuses on style transfer on the basis of non-parallel text. This is an instance of...	2017	120
6,587	Unsupervised Learning of Disentangled Representations from Video Emily Denton Department of Computer Science New York University denton@cs.nyu.edu Vighnesh Birodkar Department of Computer Science New York University vighneshbirodkar@nyu.edu Abstract We present a new model DRNET that learns disenta...	2017	121
6,588	Countering Feedback Delays in Multi-Agent Learning Zhengyuan Zhou Stanford University zyzhou@stanford.edu Panayotis Mertikopoulos Univ. Grenoble Alpes, CNRS, Inria, LIG panayotis.mertikopoulos@imag.fr Nicholas Bambos Stanford University bambos@stanford.edu Peter Glynn Stanford University glynn@s...	2017	122
6,589	Afﬁnity Clustering: Hierarchical Clustering at Scale MohammadHossein Bateni Google Research bateni@google.com Soheil Behnezhad∗ University of Maryland soheil@cs.umd.edu Mahsa Derakhshan∗ University of Maryland mahsaa@cs.umd.edu MohammadTaghi Hajiaghayi∗ University of Maryland hajiagha@cs.umd.edu...	2017	123
6,590	Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks Federico Monti Università della Svizzera italiana Lugano, Switzerland federico.monti@usi.ch Michael M. Bronstein Università della Svizzera italiana Lugano, Switzerland michael.bronstein@usi.ch Xavier Bresson School of Computer ...	2017	124
6,591	Maximizing Subset Accuracy with Recurrent Neural Networks in Multi-label Classiﬁcation Jinseok Nam1, Eneldo Loza Mencía1, Hyunwoo J. Kim2, and Johannes Fürnkranz1 1Knowledge Engineering Group, TU Darmstadt 2Department of Computer Sciences, University of Wisconsin-Madison Abstract Multi-label classiﬁcation i...	2017	125
6,592	f-GANs in an Information Geometric Nutshell Richard Nock†,‡,§ Zac Cranko‡,† Aditya Krishna Menon†,‡ Lizhen Qu†,‡ Robert C. Williamson‡,† †Data61, ‡the Australian National University and §the University of Sydney {firstname.lastname, aditya.menon, bob.williamson}@data61.csiro.au Abstract Nowozin et al ...	2017	126
6,593	Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples Haw-Shiuan Chang, Erik Learned-Miller, Andrew McCallum University of Massachusetts, Amherst 140 Governors Dr., Amherst, MA 01003 {hschang,elm,mccallum}@cs.umass.edu Abstract Self-paced learning and hard example mining...	2017	127
6,594	SchNet: A continuous-ﬁlter convolutional neural network for modeling quantum interactions K. T. Schütt1∗, P.-J. Kindermans1, H. E. Sauceda2, S. Chmiela1 A. Tkatchenko3, K.-R. Müller1,4,5† 1 Machine Learning Group, Technische Universität Berlin, Germany 2 Theory Department, Fritz-Haber-Institut der Max-Planck-...	2017	128
6,595	GibbsNet: Iterative Adversarial Inference for Deep Graphical Models Alex Lamb R Devon Hjelm Yaroslav Ganin Joseph Paul Cohen Aaron Courville Yoshua Bengio Abstract Directed latent variable models that formulate the joint distribution as p(x, z) = p(z)p(x \| z) have the advantage of fast and exact sam...	2017	129
6,596	Scalable L´evy Process Priors for Spectral Kernel Learning Phillip A. Jang Andrew E. Loeb Matthew B. Davidow Andrew Gordon Wilson Cornell University Abstract Gaussian processes are rich distributions over functions, with generalization properties determined by a kernel function. When used for long-range...	2017	13
6,597	Bayesian GAN Yunus Saatchi Uber AI Labs Andrew Gordon Wilson Cornell University Abstract Generative adversarial networks (GANs) can implicitly learn rich distributions over images, audio, and data which are hard to model with an explicit likelihood. We present a practical Bayesian formulation for unsupe...	2017	130
6,598	Alternating minimization for dictionary learning with random initialization Niladri S. Chatterji University of California, Berkeley chatterji@berkeley.edu Peter L. Bartlett University of California, Berkeley peter@berkeley.edu Abstract We present theoretical guarantees for an alternating minimization ...	2017	131
6,599	Sparse Embedded k-Means Clustering Weiwei Liu†,♮,∗, Xiaobo Shen‡,∗, Ivor W. Tsang♮ † School of Computer Science and Engineering, The University of New South Wales ‡ School of Computer Science and Engineering, Nanyang Technological University ♮Centre for Artiﬁcial Intelligence, University of Technology Sydney ...	2017	132

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