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NIPS · 24.8k rows

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8,200	Sample-Efﬁcient Reinforcement Learning with Stochastic Ensemble Value Expansion Jacob Buckman∗ Danijar Hafner George Tucker Eugene Brevdo Honglak Lee Google Brain, Mountain View, CA, USA jacobbuckman@gmail.com, mail@danijar.com, {gjt,ebrevdo,honglak}@google.com Abstract Integrating model-free and ...	2018	954
8,201	Learning Versatile Filters for Efﬁcient Convolutional Neural Networks Yunhe Wang1, Chang Xu2, Chunjing Xu1, Chao Xu3, Dacheng Tao2 1 Huawei Noah’s Ark Lab 2 UBTECH Sydney AI Centre, SIT, FEIT, University of Sydney, Australia 3 Key Lab of Machine Perception (MOE), Cooperative Medianet Innovation Center, Scho...	2018	955
8,202	Neural Nearest Neighbors Networks Tobias Plötz Stefan Roth Department of Computer Science, TU Darmstadt Abstract Non-local methods exploiting the self-similarity of natural signals have been well studied, for example in image analysis and restoration. Existing approaches, however, rely on k-nearest neighb...	2018	956
8,203	Learning latent variable structured prediction models with Gaussian perturbations Kevin Bello Department of Computer Science Purdue University West Lafayette, IN, USA kbellome@purdue.edu Jean Honorio Department of Computer Science Purdue University West Lafayette, IN, USA jhonorio@purdue.edu Abs...	2018	957
8,204	Differentially Private Change-Point Detection Rachel Cummings Georgia Institute of Technology rachelc@gatech.edu Sara Krehbiel University of Richmond krehbiel@richmond.edu Yajun Mei Georgia Institute of Technology ymei@gatech.edu Rui Tuo Texas A&M University ruituo@tamu.edu Wanrong Zhang⇤ Ge...	2018	958
8,205	Proximal Graphical Event Models Debarun Bhattacharjya Dharmashankar Subramanian Tian Gao IBM Research Thomas J. Watson Research Center, Yorktown Heights, NY, USA {debarunb,dharmash,tgao}@us.ibm.com Abstract Event datasets involve irregular occurrences of events over the timeline and are prevalent in n...	2018	959
8,206	Generalized Zero-Shot Learning with Deep Calibration Network Shichen Liu†, Mingsheng Long†(B), Jianmin Wang†, and Michael I. Jordan♯ †School of Software, Tsinghua University, China †KLiss, MOE; BNRist; Research Center for Big Data, Tsinghua University, China ♯University of California, Berkeley, Berkeley, USA ...	2018	96
8,207	Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames Geneviève Robin Centre de Mathématiques Appliquées École Polytechnique, XPOP, INRIA 91120 Palaiseau, France genevieve.robin@polytechnique.edu Hoi-To Wai Department of SE&EM The Chinese University of Hong Kong Shatin, Hong ...	2018	960
8,208	Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels Zhilu Zhang Mert R. Sabuncu Electrical and Computer Engineering Meinig School of Biomedical Engineering Cornell University zz452@cornell.edu, msabuncu@cornell.edu Abstract Deep neural networks (DNNs) have achieved treme...	2018	961
8,209	Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing Zehong Hu Alibaba Group, Hangzhou, China HUZE0004@e.ntu.edu.sg Yitao Liang University of California, Los Angeles yliang@cs.ucla.edu Jie Zhang Nanyang Technological University ZhangJ@ntu.edu.sg Zhao Li Alibaba ...	2018	962
8,210	Fast and Effective Robustness Certiﬁcation Gagandeep Singh, Timon Gehr, Matthew Mirman, Markus Püschel, Martin Vechev Department of Computer Science ETH Zurich, Switzerland {gsingh,timon.gehr,matthew.mirman,pueschel,martin.vechev}@inf.ethz.ch Abstract We present a new method and system, called DeepZ, for ce...	2018	963
8,211	Online Structured Laplace Approximations for Overcoming Catastrophic Forgetting Hippolyt Ritter1∗ Aleksandar Botev1 David Barber1,2,3 1University College London 2Alan Turing Institute 3reinfer.io Abstract We introduce the Kronecker factored online Laplace approximation for overcoming catastrophic fo...	2018	964
8,212	Optimization over Continuous and Multi-dimensional Decisions with Observational Data Dimitris Bertsimas Sloan School of Management Massachusetts Institute of Technology Cambridge, MA 02142 dbertsim@mit.edu Christopher McCord Operations Research Center Massachusetts Institute of Technology Cambridge,...	2018	965
8,213	Neural Architecture Search with Bayesian Optimisation and Optimal Transport Kirthevasan Kandasamy, Willie Neiswanger, Jeff Schneider, Barnabás Póczos, Eric P Xing Carnegie Mellon University, Petuum Inc. {kandasamy, willie, schneide, bapoczos, epxing}@cs.cmu.edu Abstract Bayesian Optimisation (BO) refers t...	2018	966
8,214	An Information-Theoretic Analysis for Thompson Sampling with Many Actions Shi Dong Stanford University sdong15@stanford.edu Benjamin Van Roy Stanford University bvr@stanford.edu Abstract Information-theoretic Bayesian regret bounds of Russo and Van Roy [8] capture the dependence of regret on prior u...	2018	967
8,215	BML: A High-performance, Low-cost Gradient Synchronization Algorithm for DML Training Songtao Wang1,2, Dan Li1, Yang Cheng1, Jinkun Geng1, Yanshu Wang1, Shuai Wang1, Shutao Xia1,2 and Jianping Wu1 1Department of Computer Science and Technology, Tsinghua University 2Graduate School at Shenzhen, Tsinghua Univer...	2018	968
8,216	Proximal SCOPE for Distributed Sparse Learning Shen-Yi Zhao National Key Lab. for Novel Software Tech. Dept. of Comp. Sci. and Tech. Nanjing University, Nanjing 210023, China zhaosy@lamda.nju.edu.cn Gong-Duo Zhang National Key Lab. for Novel Software Tech. Dept. of Comp. Sci. and Tech. Nanjing Univers...	2018	969
8,217	Dual Policy Iteration Wen Sun1, Geoffrey J. Gordon1, Byron Boots2, and J. Andrew Bagnell3 1School of Computer Science, Carnegie Mellon University, USA 2College of Computing, Georgia Institute of Technology, USA 3Aurora Innovation, USA {wensun, ggordon, dbagnell}@cs.cmu.edu, bboots@cc.gatech.edu Abstract A...	2018	97
8,218	BinGAN: Learning Compact Binary Descriptors with a Regularized GAN Maciej Zieba Wroclaw University of Science and Technology, Tooploox maciej.zieba@pwr.edu.pl Piotr Semberecki Wroclaw University of Science and Technology, Tooploox piotr.semberecki@pwr.edu.pl Tarek El-Gaaly Voyage tarek@voyage.au...	2018	970
8,219	Incorporating Context into Language Encoding Models for fMRI Shailee Jain1 Alexander G Huth1,2 Departments of 1Computer Science & 2Neuroscience The University of Texas at Austin Austin, TX 78751 {shailee, huth}@cs.utexas.edu Abstract Language encoding models help explain language processing in the hum...	2018	971
8,220	Communication Efﬁcient Parallel Algorithms for Optimization on Manifolds Bayan Saparbayeva Department of Applied and Computational Mathematics and Statistics University of Notre Dame Notre Dame, Indiana 46556, USA bsaparba@nd.edu Michael Minyi Zhang Department of Computer Science Princeton Universit...	2018	972
8,221	Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing Chen Liang Google Brain crazydonkey200@gmail.com Mohammad Norouzi Google Brain mnorouzi@google.com Jonathan Berant Tel-Aviv University, AI2 joberant@cs.tau.ac.il Quoc Le Google Brain qvl@google.com Ni Lao SayMo...	2018	973
8,222	Context-Dependent Upper-Conﬁdence Bounds for Directed Exploration Raksha Kumaraswamy1, Matthew Schlegel1, Adam White1,2, Martha White1 1Department of Computing Science, University of Alberta; 2DeepMind {kumarasw, mkschleg}@ualberta.ca, adamwhite@google.com, whitem@ualberta.ca Abstract Directed exploration s...	2018	974
8,223	Adaptive Negative Curvature Descent with Applications in Non-convex Optimization Mingrui Liu†, Zhe Li†, Xiaoyu Wang‡, Jinfeng Yi♮, Tianbao Yang† †Department of Computer Science, The University of Iowa, Iowa City, IA 52242, USA ‡ Intellifusion ♮JD AI Research mingrui-liu, tianbao-yang@uiowa.edu Abstract Ne...	2018	975
8,224	LF-Net: Learning Local Features from Images Yuki Ono Sony Imaging Products & Solutions Inc. yuki.ono@sony.com Eduard Trulls École Polytechnique Fédérale de Lausanne eduard.trulls@epfl.ch Pascal Fua École Polytechnique Fédérale de Lausanne pascal.fua@epfl.ch Kwang Moo Yi Visual Computing Group, Uni...	2018	976
8,225	Why so gloomy? A Bayesian explanation of human pessimism bias in the multi-armed bandit task Dalin Guo Department of Cognitive Science University of California San Diego La Jolla, CA 92093 dag082@ucsd.edu Angela J. Yu Department of Cognitive Science University of California San Diego La Jolla, CA 92...	2018	977
8,226	CapProNet: Deep Feature Learning via Orthogonal Projections onto Capsule Subspaces Liheng Zhang†, Marzieh Edraki†, and Guo-Jun Qi†‡∗ †Laboratory for MAchine Perception and LEarning, University of Central Florida http://maple.cs.ucf.edu ‡Huawei Cloud, Seattle, USA Abstract In this paper, we formalize the...	2018	978
8,227	Robust Subspace Approximation in a Stream Roie Levin1 roiel@cs.cmu.edu Anish Sevekari2 asevekar@andrew.cmu.edu David P. Woodruff1 dwoodruf@cs.cmu.edu 1 Computer Science Department, Carnegie Mellon University, Pittsburgh, PA 15213 2 Department of Mathematical Sciences, Carnegie Mellon University, Pittsbu...	2018	979
8,228	Recurrently Controlled Recurrent Networks Yi Tay1, Luu Anh Tuan2, and Siu Cheung Hui3 1,3Nanyang Technological University 2Institute for Infocomm Research ytay017@e.ntu.edu.sg1 at.luu@i2r.a-star.edu.sg2 asschui@ntu.edu.sg3 Abstract Recurrent neural networks (RNNs) such as long short-term memory and gate...	2018	98
8,229	PointCNN: Convolution On X-Transformed Points Yangyan Li†⇤ Rui Bu† Mingchao Sun† Wei Wu† Xinhan Di‡ Baoquan Chen§ †Shandong University ‡Huawei Inc. §Peking University Abstract We present a simple and general framework for feature learning from point clouds. The key to the success of CNNs is the ...	2018	980
8,230	Learning convex bounds for linear quadratic control policy synthesis Jack Umenberger Department of Information Technology Uppsala University Sweden jack.umenberger@it.uu.se Thomas B. Schön Department of Information Technology Uppsala University Sweden thomas.schon@it.uu.se Abstract Learning to...	2018	981
8,231	Manifold Structured Prediction Alessandro Rudi •,1 Carlo Ciliberto •,∗,2 Gian Maria Marconi 3 Lorenzo Rosasco 3,4 alessandro.rudi@inria.fr c.ciliberto@imperial.ac.uk gian.maria.marconi@iit.it lrosasco@mit.edu 1INRIA - Département d’informatique, École Normale Supérieure - PSL Research University, Pari...	2018	982
8,232	Efﬁcient Gradient Computation for Structured Output Learning with Rational and Tropical Losses Corinna Cortes Google Research New York, NY 10011 corinna@google.com Vitaly Kuznetsov Google Research New York, NY 10011 vitalyk@google.com Mehryar Mohri Courant Institute and Google Research New York,...	2018	983
8,233	Mean-ﬁeld theory of graph neural networks in graph partitioning Tatsuro Kawamoto, Masashi Tsubaki Artiﬁcial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology, 2-3-26 Aomi, Koto-ku, Tokyo, Japan {kawamoto.tatsuro, tsubaki.masashi}@aist.go.jp Tomoyuki Obuchi De...	2018	984
8,234	Adversarially Robust Generalization Requires More Data Ludwig Schmidt UC Berkeley ludwig@berkeley.edu Shibani Santurkar MIT shibani@mit.edu Dimitris Tsipras MIT tsipras@mit.edu Kunal Talwar Google Brain kunal@google.com Aleksander M ˛adry MIT madry@mit.edu Abstract Machine learning m...	2018	985
8,235	Assessing Generative Models via Precision and Recall Mehdi S. M. Sajjadi∗ MPI for Intelligent Systems, Max Planck ETH Center for Learning Systems Olivier Bachem Google Brain Mario Lucic Google Brain Olivier Bousquet Google Brain Sylvain Gelly Google Brain Abstract Recent advances in generati...	2018	986
8,236	Improved Network Robustness with Adversary Critic Alexander Matyasko, Lap-Pui Chau School of Electrical and Electronic Engineering Nanyang Technological University, Singapore aliaksan001@ntu.edu.sg, elpchau@ntu.edu.sg Abstract Ideally, what confuses neural network should be confusing to humans. However, ...	2018	987
8,237	Fast deep reinforcement learning using online adjustments from the past Steven S. Hansen ∗, Pablo Sprechmann ∗, Alexander Pritzel ∗, André Barreto, Charles Blundell {stevenhansen,psprechmann,apritzel,andrebarreto,cblundell}@google.com DeepMind Abstract We propose Ephemeral Value Adjusments (EVA): a means of...	2018	988
8,238	A Practical Algorithm for Distributed Clustering and Outlier Detection∗ Jiecao Chen Indiana University Bloomington Bloomington, IN jiecchen@indiana.edu Erfan Sadeqi Azer Indiana University Bloomington Bloomington, IN esadeqia@indiana.edu Qin Zhang Indiana University Bloomington Bloomington, IN ...	2018	989
8,239	Modelling sparsity, heterogeneity, reciprocity and community structure in temporal interaction data Xenia Miscouridou1, François Caron1, Yee Whye Teh1,2 1Department of Statistics, University of Oxford 2DeepMind {miscouri, caron, y.w.teh}@stats.ox.ac.uk Abstract We propose a novel class of network models f...	2018	99
8,240	How Much Restricted Isometry is Needed In Nonconvex Matrix Recovery? Richard Y. Zhang University of California, Berkeley ryz@alum.mit.edu Cédric Josz University of California, Berkeley cedric.josz@gmail.com Somayeh Sojoudi University of California, Berkeley sojoudi@berkeley.edu Javad Lavaei Univ...	2018	990
8,241	Limited memory Kelley’s Method Converges for Composite Convex and Submodular Objectives Song Zhou Cornell University sz557@cornell.edu Swati Gupta Georgia Institute of Technology swatig@gatech.edu Madeleine Udell Cornell University udell@cornell.edu Abstract The original simplicial method (OSM),...	2018	991
8,242	Towards Understanding Acceleration Tradeoff between Momentum and Asynchrony in Nonconvex Stochastic Optimization Tianyi Liu School of Industrial and System Engineering Georgia Institute of Technology Atlanta, GA 30332 tliu341@gatech.edu Shiyang Li Harbin Institue of Technology lsydevin@gmail.com J...	2018	992
8,243	Metric on Nonlinear Dynamical Systems with Perron-Frobenius Operators Isao Ishikawa†‡, Keisuke Fujii†, Masahiro Ikeda†‡, Yuka Hashimoto†‡, Yoshinobu Kawahara†§ †RIKEN Center for Advanced Intelligence Project ‡School of Fundamental Science and Technology, Keio University §The Institute of Scientiﬁc and Industr...	2018	993
8,244	A Mathematical Model For Optimal Decisions In A Representative Democracy Malik Magdon-Ismail Department of Computer Science Rensselaer Polytechnic Institute Troy, NY 12180 magdon@cs.rpi.edu Lirong Xia Department of Computer Science Rensselaer Polytechnic Institute Troy, NY 12180 xial@cs.rpi.edu ...	2018	994
8,245	Loss Functions for Multiset Prediction Sean Welleck1,2, Zixin Yao1, Yu Gai1, Jialin Mao1, Zheng Zhang1, Kyunghyun Cho2,3 1New York University Shanghai 2New York University 3CIFAR Azrieli Global Scholar {wellecks,zixin.yao,yg1246,jialin.mao,zz,kyunghyun.cho}@nyu.edu Abstract We study the problem of multise...	2018	995
8,246	SEGA: Variance Reduction via Gradient Sketching Filip Hanzely1 Konstantin Mishchenko1 Peter Richt´arik1,2,3 1 King Abdullah University of Science and Technology, 2University of Edinburgh, 3Moscow Institute of Physics and Technology Abstract We propose a randomized ﬁrst order optimization method—SEGA (SkEt...	2018	996
8,247	Sharp Bounds for Generalized Uniformity Testing Ilias Diakonikolas University of Southern California diakonik@usc.edu Daniel M. Kane University of California, San Diego dakane@ucsd.edu Alistair Stewart University of Southern California stewart.al@gmail.com Abstract We study the problem of generali...	2018	997
8,248	Non-Local Recurrent Network for Image Restoration Ding Liu1, Bihan Wen1, Yuchen Fan1, Chen Change Loy2, Thomas S. Huang1 1University of Illinois at Urbana-Champaign 2Nanyang Technological University {dingliu2, bwen3, yuchenf4, t-huang1}@illinois.edu ccloy@ntu.edu.sg Abstract Many classic methods have ...	2018	998
8,249	Practical exact algorithm for trembling-hand equilibrium reﬁnements in games Gabriele Farina Computer Science Department Carnegie Mellon University gfarina@cs.cmu.edu Nicola Gatti DEIB Politecnico di Milano nicola.gatti@polimi.it Tuomas Sandholm Computer Science Department Carnegie Mellon Univer...	2018	999
8,250	Plan Arithmetic: Compositional Plan Vectors for Multi-Task Control Coline Devin Daniel Geng Pieter Abbeel Trevor Darrell Sergey Levine University of California, Berkeley Abstract Autonomous agents situated in real-world environments must be able to master large repertoires of skills. While a single ...	2019	1
8,251	Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization Viet Anh Nguyen Soroosh Shaﬁeezadeh-Abadeh École Polytechnique Fédérale de Lausanne, Switzerland {viet-anh.nguyen, soroosh.shafiee}@epfl.ch Man-Chung Yue The Hong Kong Polytechnic University, Hong Kong manchung.yue@polyu.edu.hk ...	2019	10
8,252	Sequential Neural Processes Gautam Singh∗ Rutgers University singh.gautam@rutgers.edu Jaesik Yoon∗ SAP jaesik.yoon01@sap.com Youngsung Son ETRI ysson@etri.re.kr Sungjin Ahn Rutgers University sungjin.ahn@rutgers.edu Abstract Neural Processes combine the strengths of neural networks and Gauss...	2019	100
8,253	Controlling Neural Level Sets Matan Atzmon, Niv Haim, Lior Yariv, Ofer Israelov, Haggai Maron, Yaron Lipman Weizmann Institute of Science Rehovot, Israel Abstract The level sets of neural networks represent fundamental properties such as decision boundaries of classiﬁers and are used to model non-linear man...	2019	1000
8,254	Learning GANs and Ensembles Using Discrepancy Ben Adlam Google Research New York, NY 10011 adlam@google.com Corinna Cortes Google Research New York, NY 10011 corinna@google.com Mehryar Mohri Google Research & CIMS New York, NY 10012 mohri@google.com Ningshan Zhang New York University New Y...	2019	1001
8,255	Neural Relational Inference with Fast Modular Meta-learning Ferran Alet, Erica Weng, Tomás Lozano Pérez, Leslie Pack Kaelbling MIT Computer Science and Artiﬁcial Intelligence Laboratory {alet,ericaw,tlp,lpk}@mit.edu Abstract Graph neural networks (GNNs) are effective models for many dynamical systems cons...	2019	1002
8,256	Identiﬁcation of Conditional Causal Effects under Markov Equivalence Amin Jaber Purdue University jaber0@purdue.edu Jiji Zhang Lingnan University jijizhang@ln.edu.hk Elias Bareinboim Columbia University eb@cs.columbia.edu Abstract Causal identiﬁcation is the problem of deciding whether a post-in...	2019	1003
8,257	Learning to Predict Layout-to-image Conditional Convolutions for Semantic Image Synthesis Xihui Liu The Chinese University of Hong Kong xihuiliu@ee.cuhk.edu.hk Guojun Yin University of Science and Technology of China gjyin91@gmail.com Jing Shao SenseTime Research shaojing@sensetime.com Xiaogang Wa...	2019	1004
8,258	Average Case Column Subset Selection for Entrywise ℓ1-Norm Loss Zhao Song∗ University of Washington magic.linuxkde@gmail.com David P. Woodruff∗ Carnegie Mellon University dwoodruf@cs.cmu.edu Peilin Zhong∗ Columbia University pz2225@columbia.edu Abstract We study the column subset selection probl...	2019	1005
8,259	Piecewise Strong Convexity of Neural Networks Tristan Milne Department of Mathematics University of Toronto Toronto, Ontario, Canada tmilne@math.toronto.edu Abstract We study the loss surface of a feed-forward neural network with ReLU nonlinearities, regularized with weight decay. We show that the regular...	2019	1006
8,260	No Pressure! Addressing the Problem of Local Minima in Manifold Learning Algorithms Max Vladymyrov Google Research mxv@google.com Abstract Nonlinear embedding manifold learning methods provide invaluable visual insights into the structure of high-dimensional data. However, due to a complicated nonconvex o...	2019	1007
8,261	Approximate Inference Turns Deep Networks into Gaussian Processes Mohammad Emtiyaz Khan RIKEN Center for AI Project Tokyo, Japan emtiyaz.khan@riken.jp Alexander Immer* † EPFL Lausanne, Switzerland alexander.immer@epfl.ch Ehsan Abedi* † EPFL Lausanne, Switzerland ehsan.abedi@epfl.ch Maciej Ko...	2019	1008
8,262	Elliptical Perturbations for Differential Privacy Matthew Reimherr ∗ Department of Statistics Pennsylvania State University University Park, PA 16802 mreimherr@psu.edu Jordan Awan † Department of Statistics Pennsylvania State University University Park, PA 16802 awan@psu.edu Abstract We study el...	2019	1009
8,263	Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask Hattie Zhou Uber hattie@uber.com Janice Lan Uber AI janlan@uber.com Rosanne Liu Uber AI rosanne@uber.com Jason Yosinski Uber AI yosinski@uber.com Abstract The recent “Lottery Ticket Hypothesis” paper by Frankle & Carbin showed...	2019	101
8,264	Inherent Tradeoffs in Learning Fair Representations Han Zhao∗ Machine Learning Department School of Computer Science Carnegie Mellon University han.zhao@cs.cmu.edu Geoffrey J. Gordon Microsoft Research, Montreal Machine Learning Department Carnegie Mellon University geoff.gordon@microsoft.com Abst...	2019	1010
8,265	SGD on Neural Networks Learns Functions of Increasing Complexity Preetum Nakkiran Harvard University Gal Kaplun Harvard University Dimitris Kalimeris Harvard University Tristan Yang Harvard University Benjamin L. Edelman Harvard University Fred Zhang Harvard University Boaz Barak Harvard U...	2019	1011
8,266	Online Continuous Submodular Maximization: From Full-Information to Bandit Feedback Mingrui Zhang† Lin Chen‡ Hamed Hassani♯ Amin Karbasi‡,♮ † Department of Statistics and Data Science, Yale University ‡ Department of Electrical Engineering, Yale University ♯Department of Electrical and Systems Engineeri...	2019	1012
8,267	Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation Viet Anh Nguyen Soroosh Shaﬁeezadeh-Abadeh École Polytechnique Fédérale de Lausanne, Switzerland {viet-anh.nguyen, soroosh.shafiee}@epfl.ch Man-Chung Yue The Hong Kong Polytechnic University, Hong Kong manchung.yu...	2019	1013
8,268	Don’t take it lightly: Phasing optical random projections with unknown operators Sidharth Gupta University of Illinois at Urbana-Champaign gupta67@illinois.edu Rémi Gribonval Univ Rennes, Inria, CNRS, IRISA remi.gribonval@inria.fr Laurent Daudet LightOn, Paris laurent@lighton.ai Ivan Dokmani´c U...	2019	1014
8,269	Visualizing the PHATE of Neural Networks Scott Gigante Comp. Biol. and Bioinf. Program Yale University New Haven, CT 06511 scott.gigante@yale.edu Adam S. Charles Princeton Neuroscience Institute Princeton University Princeton, NJ, 08544 adamsc@princeton.edu Smita Krishnaswamy Depts. of Genetics ...	2019	1015
8,270	Gate Decorator: Global Filter Pruning Method for Accelerating Deep Convolutional Neural Networks Zhonghui You 1 Peking University zhonghui@pku.edu.cn Kun Yan 1 Peking University kyan2018@pku.edu.cn Jinmian Ye Momenta jinmian.y@gmail.com Meng Ma 2, * Peking University mameng@pku.edu.cn Ping W...	2019	1016
8,271	Kalman Filter, Sensor Fusion, and Constrained Regression: Equivalences and Insights Maria Jahja Department of Statistics Carnegie Mellon University Pittsburgh, PA 15213 maria@stat.cmu.edu David Farrow Computational Biology Department Carnegie Mellon University Pittsburgh, PA 15213 dfarrow0@gmail.c...	2019	1017
8,272	Practical Deep Learning with Bayesian Principles Kazuki Osawa,1 Siddharth Swaroop,2,⇤Anirudh Jain,3,⇤,† Runa Eschenhagen,4,† Richard E. Turner,2 Rio Yokota,1 Mohammad Emtiyaz Khan5,‡. 1 Tokyo Institute of Technology, Tokyo, Japan 2 University of Cambridge, Cambridge, UK 3 Indian Institute of Technology (ISM),...	2019	1018
8,273	Deep Active Learning with a Neural Architecture Search Yonatan Geifman Technion – Israel Institute of Technology yonatan.g@cs.technion.ac.il Ran El-Yaniv Technion – Israel Institute of Technology rani@cs.technion.ac.il Abstract We consider active learning of deep neural networks. Most active learning ...	2019	1019
8,274	Fast and Flexible Multi-Task Classiﬁcation Using Conditional Neural Adaptive Processes James Requeima∗ University of Cambridge Invenia Labs jrr41@cam.ac.uk Jonathan Gordon∗ University of Cambridge jg801@cam.ac.uk John Bronskill∗ University of Cambridge jfb54@cam.ac.uk Sebastian Nowozin Google ...	2019	102
8,275	Quality Aware Generative Adversarial Networks Parimala Kancharla, Sumohana S. Channappayya Department of Electrical Engineering Indian Institute of Technology Hyderabad {ee15m17p100001, sumohana}@iith.ac.in Abstract Generative Adversarial Networks (GANs) have become a very popular tool for implicitly learni...	2019	1020
8,276	Dual Variational Generation for Low Shot Heterogeneous Face Recognition Chaoyou Fu1,2∗, Xiang Wu1∗, Yibo Hu1, Huaibo Huang1, Ran He1,2,3† 1NLPR & CRIPAC, CASIA 2University of Chinese Academy of Sciences 3Center for Excellence in Brain Science and Intelligence Technology, CAS {chaoyou.fu, rhe}@nlpr.ia.ac.cn,...	2019	1021
8,277	Off-Policy Evaluation via Off-Policy Classiﬁcation Alex Irpan1, Kanishka Rao1, Konstantinos Bousmalis2, Chris Harris1, Julian Ibarz1, Sergey Levine1,3 1Google Brain, Mountain View, USA 2DeepMind, London, UK 3University of California Berkeley, Berkeley, USA {alexirpan,kanishkarao,konstantinos,ckharris,julian...	2019	1022
8,278	Variational Temporal Abstraction Taesup Kim1,3,†, Sungjin Ahn2∗, Yoshua Bengio1∗ 1Mila, Université de Montréal, 2Rutgers University, 3Kakao Brain Abstract We introduce a variational approach to learning and inference of temporally hierarchical structure and representation for sequential data. We propose the Var...	2019	1023
8,279	Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations Vincent Sitzmann Michael Zollhöfer Gordon Wetzstein {sitzmann, zollhoefer}@cs.stanford.edu, gordon.wetzstein@stanford.edu Stanford University vsitzmann.github.io/srns/ Abstract Unsupervised learning with generati...	2019	1024
8,280	Control What You Can Intrinsically Motivated Task-Planning Agent Sebastian Blaes Marin Vlastelica Poganˇci´c Jia-Jie Zhu Georg Martius Autonomous Learning Group Max Planck Institute for Intelligent Systems Tübingen, Germany {sebastian.blaes,marin.vlastelica,jzhu,georg.martius}@tue.mpg.de Abstract ...	2019	1025
8,281	Momentum-Based Variance Reduction in Non-Convex SGD Ashok Cutkosky Google Research Mountain View, CA, USA ashok@cutkosky.com Francesco Orabona Boston University Boston, MA, USA francesco@orabona.com Abstract Variance reduction has emerged in recent years as a strong competitor to stochastic grad...	2019	1026
8,282	Adversarial Self-Defense for Cycle-Consistent GANs Dina Bashkirova 1, Ben Usman1, and Kate Saenko 1,2 1Boston University 2MIT-IBM Watson AI Lab {dbash,usmn,saenko}@bu.edu Abstract The goal of unsupervised image-to-image translation is to map images from one domain to another without the ground truth corre...	2019	1027
8,283	Ultrametric Fitting by Gradient Descent Giovanni Chierchia∗ Université Paris-Est, LIGM (UMR 8049) CNRS, ENPC, ESIEE Paris, UPEM F-93162, Noisy-le-Grand, France giovanni.chierchia@esiee.fr Benjamin Perret∗ Université Paris-Est, LIGM (UMR 8049) CNRS, ENPC, ESIEE Paris, UPEM F-93162, Noisy-le-Grand, Fran...	2019	1028
8,284	Expressive power of tensor-network factorizations for probabilistic modeling Ivan Glasser1,2∗, Ryan Sweke3, Nicola Pancotti1,2, Jens Eisert3,4, J. Ignacio Cirac1,2 1Max-Planck-Institut für Quantenoptik, D-85748 Garching 2Munich Center for Quantum Science and Technology (MCQST), D-80799 München 3Dahlem Center ...	2019	1029
8,285	A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox∗1 Timur Garipov∗2 Pavel Izmailov∗1 Dmitry Vetrov2,3 Andrew Gordon Wilson1 1 New York University 2 Samsung AI Center Moscow 3 Samsung-HSE Laboratory, National Research University Higher School of Economics Abstract We prop...	2019	103
8,286	PerspectiveNet: 3D Object Detection from a Single RGB Image via Perspective Points Siyuan Huang Department of Statistics huangsiyuan@ucla.edu Yixin Chen Department of Statistics ethanchen@ucla.edu Tao Yuan Department of Statistics taoyuan@ucla.edu Siyuan Qi Department of Computer Science syqi@...	2019	1030
8,287	Landmark Ordinal Embedding Nikhil Ghosh∗ UC Berkeley nikhil_ghosh@berkeley.edu Yuxin Chen∗ UChicago chenyuxin@uchicago.edu Yisong Yue Caltech yyue@caltech.edu Abstract In this paper, we aim to learn a low-dimensional Euclidean representation from a set of constraints of the form “item j is close...	2019	1031
8,288	On the Value of Target Data in Transfer Learning Steve Hanneke Toyota Technological Institute at Chicago steve.hanneke@gmail.com Samory Kpotufe Columbia University, Statistics skk2175@columbia.edu Abstract We aim to understand the value of additional labeled or unlabeled target data in transfer learni...	2019	1032
8,289	Machine Teaching of Active Sequential Learners Tomi Peltola tomi.peltola@aalto.fi Mustafa Mert Çelikok mustafa.celikok@aalto.fi Pedram Daee pedram.daee@aalto.fi Samuel Kaski samuel.kaski@aalto.fi Helsinki Institute for Information Technology HIIT Department of Computer Science, Aalto University, Hel...	2019	1033
8,290	Beyond Conﬁdence Regions: Tight Bayesian Ambiguity Sets for Robust MDPs Reazul Hasan Russel Department of Computer Science University of New Hampshire rrussel@cs.unh.edu Marek Petrik Department of Computer Science University of New Hampshire mpetrik@cs.unh.edu Abstract Robust MDPs (RMDPs) can be u...	2019	1034
8,291	A General Theory of Equivariant CNNs on Homogeneous Spaces Taco S. Cohen Qualcomm AI Research∗ Qualcomm Technologies Netherlands B.V. tacos@qti.qualcomm.com Mario Geiger PCSL Research Group EPFL mario.geiger@epfl.ch Maurice Weiler QUVA Lab U. of Amsterdam m.weiler@uva.nl Abstract We presen...	2019	1035
8,292	Spatial-Aware Feature Aggregation for Cross-View Image based Geo-Localization Yujiao Shi, Liu Liu, Xin Yu, Hongdong Li Australian National University, Canberra, Australia. Australian Centre for Robotic Vision, Australia. {firstname.lastname}@anu.edu.au Abstract Recent works show that it is possible to tra...	2019	1036
8,293	Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classiﬁcation Evgenii Chzhen1,2, Christophe Denis1, Mohamed Hebiri1, Luca Oneto3, Massimiliano Pontil4,5 1Université Paris-Est, 2Université Paris-Sud, 3University of Pisa, 4Istituto Italiano di Tecnologia, 5University College London evgenii.ch...	2019	1037
8,294	Tight Dimensionality Reduction for Sketching Low Degree Polynomial Kernels Michela Meister∗ Cornell University Ithaca, NY 14850 meister.michela@gmail.com Tamas Sarlos Google Research Mountain View, CA 94043 stamas@google.com David P. Woodruff† Department of Computer Science Carnegie Mellon Unive...	2019	1038
8,295	Minimum Stein Discrepancy Estimators Alessandro Barp Department of Mathematics Imperial College London a.barp16@imperial.ac.uk François-Xavier Briol Department of Statistical Science University College London f.briol@ucl.ac.uk Andrew B. Duncan Department of Mathematics Imperial College London a....	2019	1039
8,296	CPM-Nets: Cross Partial Multi-View Networks Changqing Zhang1,2, Zongbo Han1, Yajie Cui1, Huazhu Fu3, Joey Tianyi Zhou4∗, Qinghua Hu1,2 1College of Intelligence and Computing, Tianjin University, Tianjin, China 2Tianjin Key Lab of Machine Learning, Tianjin, China 3Inception Institute of Artiﬁcial Intelligence, A...	2019	104
8,297	Provably Powerful Graph Networks Haggai Maron∗ Heli Ben-Hamu∗ Hadar Serviansky∗ Yaron Lipman Weizmann Institute of Science Rehovot, Israel Abstract Recently, the Weisfeiler-Lehman (WL) graph isomorphism test was used to measure the expressive power of graph neural networks (GNN). It was shown that the ...	2019	1040
8,298	Regularized Anderson Acceleration for Off-Policy Deep Reinforcement Learning Wenjie Shi, Shiji Song, Hui Wu, Ya-Chu Hsu, Cheng Wu, Gao Huang∗ Department of Automation, Tsinghua University, Beijing, China Beijing National Research Center for Information Science and Technology (BNRist) {shiwj16, wuhui14, xuyz17...	2019	1041
8,299	Kernel Stein Tests for Multiple Model Comparison Jen Ning Lim Max Planck Institute for Intelligent Systems jlim@tuebingen.mpg.de Makoto Yamada Kyoto University, RIKEN AIP makoto.yamada@riken.jp Bernhard Schölkopf Max Planck Institute for Intelligent Systems bs@tuebingen.mpg.de Wittawat Jitkrittum ...	2019	1042

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