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NIPS · 24.8k rows

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7,900	Insights on representational similarity in neural networks with canonical correlation Ari S. Morcos∗‡ DeepMind† arimorcos@gmail.com Maithra Raghu∗‡ Google Brain, Cornell University maithrar@gmail.com Samy Bengio Google Brain bengio@google.com Abstract Comparing different neural network represent...	2018	684
7,901	Efﬁcient nonmyopic batch active search Shali Jiang CSE, WUSTL St. Louis, MO 63130 jiang.s@wustl.edu Gustavo Malkomes CSE, WUSTL St. Louis, MO 63130 luizgustavo@wustl.edu Matthew Abbott CSE, WUSTL St. Louis, MO 63130 mbabbott@wustl.edu Benjamin Moseley Tepper School of Business, CMU and Rel...	2018	685
7,902	Learning safe policies with expert guidance Jessie Huang1 Fa Wu12 Doina Precup1 Yang Cai1 1School of Computer Science, McGill University 2Zhejiang Demetics Medical Technology {jiexi.huang,fa.wu2}@mcgill.ca, {dprecup,cai}@cs.mcgill.ca Abstract We propose a framework for ensuring safe behavior of a rein...	2018	686
7,903	Fast Similarity Search via Optimal Sparse Lifting Wenye Li1,2,∗, Jingwei Mao1, Yin Zhang1, Shuguang Cui1,2 1 The Chinese University of Hong Kong, Shenzhen, China 2 Shenzhen Research Institute of Big Data, Shenzhen, China {wyli,yinzhang,shuguangcui}@cuhk.edu.cn, 216019005@link.cuhk.edu.cn Abstract Similarity...	2018	687
7,904	Differentially Private Robust Low-Rank Approximation Raman Arora Johns Hopkins University Baltimore, MD-21201 arora@cs.jhu.edu Vladimir Braverman Johns Hopkins University Baltimore, MD-21201 vova@cs.jhu.edu Jalaj Upadhyay Johns Hopkins University Baltimore, MD-21201 jalaj@jhu.edu Abstract ...	2018	688
7,905	Evidential Deep Learning to Quantify Classiﬁcation Uncertainty Murat Sensoy Department of Computer Science Ozyegin University, Turkey murat.sensoy@ozyegin.edu.tr Lance Kaplan US Army Research Lab Adelphi, MD 20783, USA lkaplan@ieee.org Melih Kandemir Bosch Center for Artiﬁcial Intelligence Rober...	2018	689
7,906	Hessian-based Analysis of Large Batch Training and Robustness to Adversaries Zhewei Yao1⇤Amir Gholami1⇤Qi Lei2 Kurt Keutzer1 Michael W. Mahoney1 1 University of California at Berkeley, {zheweiy, amirgh, keutzer and mahoneymw}@berkeley.edu 2 University of Texas at Austin, leiqi@ices.utexas.edu Abstract L...	2018	69
7,907	A Game-Theoretic Approach to Recommendation Systems with Strategic Content Providers Omer Ben-Porat and Moshe Tennenholtz Technion - Israel Institute of Technology Haifa 32000 Israel {omerbp@campus,moshe@ie}.technion.ac.il Abstract We introduce a game-theoretic approach to the study of recommendation syst...	2018	690
7,908	Frequency-Domain Dynamic Pruning for Convolutional Neural Networks Zhenhua Liu1, Jizheng Xu2, Xiulian Peng2, Ruiqin Xiong1 1Institute of Digital Media, School of Electronic Engineering and Computer Science, Peking University 2Microsoft Research Asia liu-zh@pku.edu.cn, jzxu@microsoft.com, xipe@microsoft.com, r...	2018	691
7,909	Adaptive Path-Integral Autoencoder: Representation Learning and Planning for Dynamical Systems Jung-Su Ha, Young-Jin Park, Hyeok-Joo Chae, Soon-Seo Park, and Han-Lim Choi Department of Aerospace Engineering & KI for Robotics, KAIST Daejeon 305-701, Republic of Korea {{jsha, yjpark, hjchae, sspark}@lics., hanl...	2018	692
7,910	Testing for Families of Distributions via the Fourier Transform∗ Clément L. Canonne Stanford University ccanonne@stanford.edu Ilias Diakonikolas University of Southern California diakonik@usc.edu Alistair Stewart University of Southern California stewart.al@gmail.com Abstract We study the genera...	2018	693
7,911	A Uniﬁed Framework for Extensive-Form Game Abstraction with Bounds Christian Kroer Computer Science Department Pittsburgh, PA 15213 ckroer@cs.cmu.edu Tuomas Sandholm Computer Science Department Pittsburgh, PA 15213 sandholm@cs.cmu.edu Abstract Abstraction has long been a key component in the pract...	2018	694
7,912	Model-Agnostic Private Learning Raef Bassily∗ Om Thakkar† Abhradeep Thakurta‡ Abstract We design differentially private learning algorithms that are agnostic to the learning model assuming access to a limited amount of unlabeled public data. First, we provide a new differentially private algorithm for answe...	2018	695
7,913	Towards Text Generation with Adversarially Learned Neural Outlines Sandeep Subramanian1,2,4∗, Sai Rajeswar1,2,5, Alessandro Sordoni4, Adam Trischler4, Aaron Courville1,2,6, Christopher Pal1,3,5 1Montr´eal Institute for Learning Algorithms, 2Universit´e de Montr´eal, 3 ´Ecole Polytechnique de Montr´eal, 4Micro...	2018	696
7,914	FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network Aditya Kusupati†, Manish Singh§, Kush Bhatia‡, Ashish Kumar‡, Prateek Jain† and Manik Varma† †Microsoft Research India §Indian Institute of Technology Delhi ‡University of California Berkeley {t-vekusu,prajain,manik}...	2018	697
7,915	Bipartite Stochastic Block Models with Tiny Clusters Stefan Neumann University of Vienna Faculty of Computer Science Vienna, Austria stefan.neumann@univie.ac.at Abstract We study the problem of ﬁnding clusters in random bipartite graphs. We present a simple two-step algorithm which provably ﬁnds even ti...	2018	698
7,916	Conditional Adversarial Domain Adaptation Mingsheng Long†, Zhangjie Cao†, 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 {mingsheng, jimwang}@...	2018	699
7,917	Contour location via entropy reduction leveraging multiple information sources Alexandre N. Marques Department of Aeronautics and Astronautics Massachusetts Institute of Technology Cambridge, MA 02139 noll@mit.edu Remi R. Lam Center for Computational Engineering Massachusetts Institute of Technology ...	2018	7
7,918	Adaptive Online Learning in Dynamic Environments Lijun Zhang, Shiyin Lu, Zhi-Hua Zhou National Key Laboratory for Novel Software Technology Nanjing University, Nanjing 210023, China {zhanglj, lusy, zhouzh}@lamda.nju.edu.cn Abstract In this paper, we study online convex optimization in dynamic environmen...	2018	70
7,919	Stochastic Expectation Maximization with Variance Reduction Jianfei Chen†, Jun Zhu†∗, Yee Whye Teh‡ and Tong Zhang§ † Dept. of Comp. Sci. & Tech., BNRist Center, State Key Lab for Intell. Tech. & Sys., Institute for AI, THBI Lab, Tsinghua University, Beijing, 100084, China ‡ Department of Statistics, Universi...	2018	700
7,920	Bayesian Nonparametric Spectral Estimation Felipe Tobar Universidad de Chile ftobar@dim.uchile.cl Abstract Spectral estimation (SE) aims to identify how the energy of a signal (e.g., a time series) is distributed across different frequencies. This can become particularly challenging when only partial and ...	2018	701
7,921	A Simple Uniﬁed Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks Kimin Lee1, Kibok Lee2, Honglak Lee3,2, Jinwoo Shin1,4 1Korea Advanced Institute of Science and Technology (KAIST) 2University of Michigan 3Google Brain 4AItrics Abstract Detecting test samples drawn sufﬁciently ...	2018	702
7,922	Breaking the Span Assumption Yields Fast Finite-Sum Minimization∗ Robert Hannah†1, Yanli Liu‡1, Daniel O’Connor§2, and Wotao Yin¶1 1Department of Mathematics, University of California, Los Angeles 2Department of Mathematics, University of San Francisco Abstract In this paper, we show that SVRG and SARAH can...	2018	703
7,923	Differential Privacy for Growing Databases Rachel Cummings⇤ Georgia Institute of Technology rachelc@gatech.edu Sara Krehbiel⇤ University of Richmond krehbiel@richmond.edu Kevin A. Lai⇤ Georgia Institute of Technology kevinlai@gatech.edu Uthaipon Tantipongpipat⇤ Georgia Institute of Technology ta...	2018	704
7,924	Learning Pipelines with Limited Data and Domain Knowledge: A Study in Parsing Physics Problems Mrinmaya Sachan♣ Avinava Dubey♣ Tom Mitchell♣ Dan Roth♠ Eric P. Xing♣♦ ♣Machine Learning Department, School of Computer Science, Carnegie Mellon University ♠Department of Computer and Information Science, Univ...	2018	705
7,925	Theoretical guarantees for the EM algorithm when applied to mis-speciﬁed Gaussian mixture models Raaz Dwivedi⋆ Nhat Ho⋆ Koulik Khamaru⋆ UC Berkeley {raaz.rsk, minhnhat, koulik}@berkeley.edu Martin J. Wainwright UC Berkeley Voleon Group wainwrig@berkeley.edu Michael I. Jordan UC Berkeley jordan...	2018	706
7,926	Online Improper Learning with an Approximation Oracle⇤ Elad Hazan Princeton University & Google AI Princeton ehazan@cs.princeton.edu Wei Hu Princeton University huwei@cs.princeton.edu Yuanzhi Li Stanford University yuanzhil@stanford.edu Zhiyuan Li Princeton University zhiyuanli@cs.princeton.ed...	2018	707
7,927	Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise Dan Hendrycks∗ University of California, Berkeley hendrycks@berkeley.edu Mantas Mazeika∗ University of Chicago mantas@ttic.edu Duncan Wilson Foundational Research Institute duncanw@nevada.unr.edu Kevin Gimpel Toyota Te...	2018	708
7,928	Multi-Task Zipping via Layer-wise Neuron Sharing Xiaoxi He ETH Zurich hex@ethz.ch Zimu Zhou∗ ETH Zurich zzhou@tik.ee.ethz.ch Lothar Thiele ETH Zurich thiele@ethz.ch Abstract Future mobile devices are anticipated to perceive, understand and react to the world on their own by running multiple corr...	2018	709
7,929	Learning in Games with Lossy Feedback Zhengyuan Zhou Stanford University zyzhou@stanford.edu Panayotis Mertikopoulos Univ. Grenoble Alpes, CNRS, Inria, LIG panayotis.mertikopoulos@imag.fr Susan Athey Stanford University athey@stanford.edu Nicholas Bambos Stanford University bambos@stanford.edu ...	2018	71
7,930	Practical Deep Stereo (PDS): Toward applications-friendly deep stereo matching. Stepan Tulyakov Space Engineering Center at École Polytechnique Fédérale de Lausanne stepan.tulyakov@epfl.ch Anton Ivanov Space Engineering Center at École Polytechnique Fédérale de Lausanne anton.ivanov@epfl.ch Francois...	2018	710
7,931	Masking: A New Perspective of Noisy Supervision Bo Han∗1,2, Jiangchao Yao∗3,1, Gang Niu2, Mingyuan Zhou4, Ivor W. Tsang1, Ya Zhang3, Masashi Sugiyama2,5 1Centre for Artiﬁcial Intelligence, University of Technology Sydney 2Center for Advanced Intelligence Project, RIKEN 3Cooperative Medianet Innovation Center,...	2018	711
7,932	Learning to Multitask Yu Zhang1, Ying Wei2, Qiang Yang1 1HKUST 2Tencent AI Lab yu.zhang.ust@gmail.com judywei@tencent.com qyang@cse.ust.hk Abstract Multitask learning has shown promising performance in many applications and many multitask models have been proposed. In order to identify an effective multit...	2018	712
7,933	Thwarting Adversarial Examples: An L0-Robust Sparse Fourier Transform Mitali Bafna ∗ School of Engineering & Applied Sciences Harvard University Cambridge, MA USA mitalibafna@g.harvard.edu Jack Murtagh ∗ School of Engineering & Applied Sciences Harvard University Cambridge, MA USA jmurtagh@g.harva...	2018	713
7,934	Constant Regret, Generalized Mixability, and Mirror Descent Zakaria Mhammedi Research School of Computer Science Australian National University and DATA61 zak.mhammedi@anu.edu.au Robert C. Williamson Research School of Computer Science Australian National University and DATA61 bob.williamson@anu.edu.a...	2018	714
7,935	Dual Principal Component Pursuit: Improved Analysis and Efﬁcient Algorithms Zhihui Zhu MINDS Johns Hopkins University zzhu29@jhu.edu Yifan Wang SIST ShanghaiTech University wangyf@shanghaitech.edu.cn Daniel Robinson AMS Johns Hopkins University daniel.p.robinson@jhu.edu Daniel Naiman AMS ...	2018	715
7,936	Generative Modeling for Protein Structures Namrata Anand Bioengineering Department, Stanford namrataa@stanford.edu Po-Ssu Huang Bioengineering Department, Stanford possu@stanford.edu Abstract Analyzing the structure and function of proteins is a key part of understanding biology at the molecular and c...	2018	716
7,937	Found Graph Data and Planted Vertex Covers Austin R. Benson Cornell University arb@cs.cornell.edu Jon Kleinberg Cornell University kleinber@cs.cornell.edu Abstract A typical way in which network data is recorded is to measure all interactions involving a speciﬁed set of core nodes, which produces a gr...	2018	717
7,938	Fast Estimation of Causal Interactions using Wold Processes Flavio Figueiredo Guilherme Borges Pedro O. S. Vaz de Melo Renato Assunc¸˜ao Universidade Federal de Minas Gerais (UFMG) {flaviovdf, guilherme.borges, olmo, assuncao}@dcc.ufmg.br Reproducibility: http://github.com/flaviovdf/granger-busca Abst...	2018	718
7,939	Relating Leverage Scores and Density using Regularized Christoffel Functions Edouard Pauwels IRIT-AOC Université Toulouse 3 Paul Sabatier Toulouse, France Francis Bach INRIA Ecole Normale Supérieure PSL Research University Paris, France Jean-Philippe Vert Google Brain CBIO Mines ParisTech ...	2018	719
7,940	Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes Loucas Pillaud-Vivien INRIA - Ecole Normale Supérieure PSL Research University loucas.pillaud-vivien@inria.fr Alessandro Rudi INRIA - Ecole Normale Supérieure PSL Research University alessandro.rudi...	2018	72
7,941	Online Adaptive Methods, Universality and Acceleration Kﬁr Y. Levy ETH Zurich yehuda.levy@inf.ethz.ch Alp Yurtsever EPFL alp.yurtsever@epfl.ch Volkan Cevher EPFL volkan.cevher@epfl.ch Abstract We present a novel method for convex unconstrained optimization that, without any modiﬁcations, ensur...	2018	720
7,942	Reparameterization Gradient for Non-differentiable Models Wonyeol Lee Hangyeol Yu Hongseok Yang School of Computing, KAIST Daejeon, South Korea {wonyeol, yhk1344, hongseok.yang}@kaist.ac.kr Abstract We present a new algorithm for stochastic variational inference that targets at models with non-diffe...	2018	721
7,943	Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents Edoardo Conti⇤ Vashisht Madhavan⇤ Felipe Petroski Such Joel Lehman Kenneth O. Stanley Jeff Clune Uber AI Labs Abstract Evolution strategies (ES) are a family of black-box optimi...	2018	722
7,944	Optimistic Optimization of a Brownian Jean-Bastien Grill Michal Valko R´emi Munos SequeL team, INRIA Lille - Nord Europe, France and DeepMind Paris, France jbgrill@google.com michal.valko@inria.fr munos@google.com Abstract We address the problem of optimizing a Brownian motion. We consider a (random) ...	2018	723
7,945	Generalizing Tree Probability Estimation via Bayesian Networks Cheng Zhang Computational Biology Program Fred Hutchinson Cancer Research Center Seattle, WA 98109 chengz23@fredhutch.org Frederick A. Matsen IV Computational Biology Program Fred Hutchinson Cancer Research Center Seattle, WA 98109 mat...	2018	724
7,946	Safe Active Learning for Time-Series Modeling with Gaussian Processes Christoph Zimmer Mona Meister Duy Nguyen-Tuong Bosch Center for Artiﬁcial Intelligence, Renningen, Germany {christoph.zimmer,mona.meister,duy.nguyen-tuong}@de.bosch.com Abstract Learning time-series models is useful for many applicati...	2018	725
7,947	Computing Kantorovich-Wasserstein Distances on d-dimensional histograms using (d + 1)-partite graphs Gennaro Auricchio, Stefano Gualandi, Marco Veneroni Università degli Studi di Pavia, Dipartimento di Matematica “F. Casorati" gennaro.auricchio01@universitadipavia.it, stefano.gualandi@unipv.it, marco.veneroni...	2018	726
7,948	SimplE Embedding for Link Prediction in Knowledge Graphs Seyed Mehran Kazemi University of British Columbia Vancouver, BC, Canada smkazemi@cs.ubc.ca David Poole University of British Columbia Vancouver, BC, Canada poole@cs.ubc.ca Abstract Knowledge graphs contain knowledge about the world and prov...	2018	727
7,949	Bounded-Loss Private Prediction Markets Rafael Frongillo Colorado Boulder raf@colorado.edu Bo Waggoner Microsoft Research bwag@colorado.edu Abstract Prior work has investigated variations of prediction markets that preserve participants’ (differential) privacy, which formed the basis of useful mechanism...	2018	728
7,950	Statistical mechanics of low-rank tensor decomposition Jonathan Kadmon Department of Applied Physics, Stanford University kadmonj@stanford.edu Surya Ganguli Department of Applied Physics, Stanford University and Google Brain, Mountain View, CA sganguli@stanford.edu Abstract Often, large, high dimensio...	2018	729
7,951	Multimodal Generative Models for Scalable Weakly-Supervised Learning Mike Wu Department of Computer Science Stanford University Stanford, CA 94025 wumike@stanford.edu Noah Goodman Departments of Computer Science and Psychology Stanford University Stanford, CA 94025 ngoodman@stanford.edu Abstract...	2018	73
7,952	A theory on the absence of spurious solutions for nonconvex and nonsmooth optimization C. Josz EECS, UC Berkeley cedric.josz@gmail.com Y. Ouyang IEOR, UC Berkeley ouyangyii@gmail.com R. Y. Zhang IEOR, UC Berkeley ryz@berkeley.edu J. Lavaei IEOR, UC Berkeley lavaei@berkeley.edu S. Sojoudi E...	2018	730
7,953	A Structured Prediction Approach for Label Ranking Anna Korba, Alexandre Garcia, Florence d’Alché-Buc LTCI, Télécom ParisTech Université Paris-Saclay Paris, France firstname.lastname@telecom-paristech.fr Abstract We propose to solve a label ranking problem as a structured output regression task. In this...	2018	731
7,954	Geometrically Coupled Monte Carlo Sampling Mark Rowland∗ University of Cambridge mr504@cam.ac.uk Krzysztof Choromanski* Google Brain Robotics kchoro@google.com François Chalus University of Cambridge chalusf3@gmail.com Aldo Pacchiano University of California, Berkeley pacchiano@berkeley.edu Ta...	2018	732
7,955	The Lingering of Gradients: How to Reuse Gradients over Time Zeyuan Allen-Zhu∗ Microsoft Research AI Redmond, WA 98052 zeyuan@csail.mit.edu David Simchi-Levi∗ MIT Cambridge, MA 02139 dslevi@mit.edu Xinshang Wang∗ MIT Cambridge, MA 02139 xinshang@mit.edu Abstract Classically, the time compl...	2018	733
7,956	Submodular Maximization via Gradient Ascent: The Case of Deep Submodular Functions Wenruo Bai‡, William S Noble∗$, Jeff A. Bilmes‡$ Depts. of Electrical & Computer Engineering‡, Computer Science and Engineering$, and Genome Sciences∗ Seattle, WA 98195 {wrbai,wnoble,bilmes}@uw.edu Abstract We study the pro...	2018	734
7,957	Sparsiﬁed SGD with Memory Sebastian U. Stich Jean-Baptiste Cordonnier Martin Jaggi Machine Learning and Optimization Laboratory (MLO) EPFL, Switzerland Abstract Huge scale machine learning problems are nowadays tackled by distributed optimization algorithms, i.e. algorithms that leverage the compute power...	2018	735
7,958	Convergence of Cubic Regularization for Nonconvex Optimization under KŁ Property Yi Zhou Department of ECE The Ohio State University zhou.1172@osu.edu Zhe Wang Department of ECE The Ohio State University wang.10982@osu.edu Yingbin Liang Department of ECE The Ohio State University liang.889@osu...	2018	736
7,959	Model Agnostic Supervised Local Explanations Gregory Plumb CMU gdplumb@andrew.cmu.edu Denali Molitor UCLA dmolitor@math.ucla.edu Ameet Talwalkar CMU talwalkar@cmu.edu Abstract Model interpretability is an increasingly important component of practical machine learning. Some of the most common forms...	2018	737
7,960	Mental Sampling in Multimodal Representations Jian-Qiao Zhu Department of Psychology University of Warwick j.zhu@warwick.ac.uk Adam N. Sanborn Department of Psychology University of Warwick a.n.sanborn@warwick.ac.uk Nick Chater Behavioural Science Group Warwick Business School nick.chater@wbs.ac...	2018	738
7,961	Nonparametric learning from Bayesian models with randomized objective functions Simon Lyddon Department of Statistics University of Oxford Oxford, UK lyddon@stats.ox.ac.uk Stephen Walker Department of Mathematics University of Texas at Austin Austin, TX s.g.walker@math.utexas.edu Chris Holmes ...	2018	739
7,962	Multi-Class Learning: From Theory to Algorithm Jian Li1,2, Yong Liu1∗, Rong Yin1,2, Hua Zhang1, Lizhong Ding5, Weiping Wang1,3,4 1Institute of Information Engineering, Chinese Academy of Sciences 2School of Cyber Security, University of Chinese Academy of Sciences 3National Engineering Research Center for Infor...	2018	74
7,963	On the Dimensionality of Word Embedding Zi Yin Stanford University s0960974@gmail.com Yuanyuan Shen Microsoft Corp. & Stanford University Yuanyuan.Shen@microsoft.com Abstract In this paper, we provide a theoretical understanding of word embedding and its dimensionality. Motivated by the unitary-invari...	2018	740
7,964	Large Scale computation of Means and Clusters for Persistence Diagrams using Optimal Transport Théo Lacombe Datashape Inria Saclay theo.lacombe@inria.fr Marco Cuturi Google Brain, and CREST, ENSAE cuturi@google.com Steve Oudot Datashape Inria Saclay steve.oudot@inria.fr Abstract Persistenc...	2018	741
7,965	Probabilistic Matrix Factorization for Automated Machine Learning Nicolo Fusi, Rishit Sheth Microsoft Research, New England {nfusi,rishet}@microsoft.com Melih Elibol∗ EECS, University of California, Berkeley elibol@cs.berkeley.edu Abstract In order to achieve state-of-the-art performance, modern machi...	2018	742
7,966	REFUEL: Exploring Sparse Features in Deep Reinforcement Learning for Fast Disease Diagnosis Yu-Shao Peng HTC Research & Healthcare ys_peng@htc.com Kai-Fu Tang HTC Research & Healthcare kevin_tang@htc.com Hsuan-Tien Lin Department of CSIE, National Taiwan University htlin@csie.ntu.edu.tw Edward Y...	2018	743
7,967	Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data Dominik Linzner1 and Heinz Koeppl1,2 1Department of Electrical Engineering and Information Technology 2Department of Biology Technische Universität Darmstadt {dominik.linzner, heinz.koeppl}@...	2018	744
7,968	Norm-Ranging LSH for Maximum Inner Product Search Xiao Yan, Jinfeng Li, Xinyan Dai, Hongzhi Chen, James Cheng Department of Computer Science The Chinese University of Hong Kong Shatin, Hong Kong {xyan, jfli, xydai, hzchen, jcheng}@cse.cuhk.edu.hk Abstract Neyshabur and Srebro proposed SIMPLE-LSH [2015],...	2018	745
7,969	Generalizing Point Embeddings using the Wasserstein Space of Elliptical Distributions Boris Muzellec CREST, ENSAE boris.muzellec@ensae.fr Marco Cuturi Google Brain and CREST, ENSAE cuturi@google.com Abstract Embedding complex objects as vectors in low dimensional spaces is a longstanding problem in ...	2018	746
7,970	Dirichlet-based Gaussian Processes for Large-scale Calibrated Classiﬁcation Dimitrios Milios EURECOM Sophia Antipolis, France dimitrios.milios@eurecom.fr Raffaello Camoriano LCSL IIT (Italy) & MIT (USA) raffaello.camoriano@iit.it Pietro Michiardi EURECOM Sophia Antipolis, France pietro.michiar...	2018	747
7,971	Latent Alignment and Variational Attention Yuntian Deng∗ Yoon Kim∗ Justin Chiu Demi Guo Alexander M. Rush {dengyuntian@seas,yoonkim@seas,justinchiu@g,dguo@college,srush@seas}.harvard.edu School of Engineering and Applied Sciences Harvard University Cambridge, MA, USA Abstract Neural attention has ...	2018	748
7,972	The Pessimistic Limits and Possibilities of Margin-based Losses in Semi-supervised Learning Jesse H. Krijthe Radboud University, The Netherlands jkrijthe@gmail.com Marco Loog Delft University of Technology, The Netherlands University of Copenhagen, Denmark m.loog@tudelft.nl Abstract Consider a class...	2018	749
7,973	Learning and Inference in Hilbert Space with Quantum Graphical Models Siddarth Srinivasan College of Computing Georgia Tech Atlanta, GA 30332 sidsrini@gatech.edu Carlton Downey Department of Machine Learning Carnegie Mellon University Pittsburgh, PA 15213 cmdowney@cs.cmu.edu Byron Boots Colleg...	2018	75
7,974	Porcupine Neural Networks: Approximating Neural Network Landscapes Soheil Feizi Department of Computer Science University of Maryland, College Park sfeizi@cs.umd.edu Hamid Javadi Department of Electrical and Computer Engineering Rice University hrhakim@rice.edu Jesse Zhang Department of Electrical...	2018	750
7,975	On the Local Hessian in Back-propagation Huishuai Zhang Microsoft Research Asia Beijing, 100080 Wei Chen Microsoft Research Asia Beijing, 100080 Tie-Yan Liu Microsoft Research Asia Beijing, 100080 Abstract Back-propagation (BP) is the foundation for successfully training deep neural networks. Ho...	2018	751
7,976	Inﬁnite-Horizon Gaussian Processes Arno Solin∗ Aalto University arno.solin@aalto.fi James Hensman PROWLER.io james@prowler.io Richard E. Turner University of Cambridge ret26@cam.ac.uk Abstract Gaussian processes provide a ﬂexible framework for forecasting, removing noise, and interpreting long t...	2018	752
7,977	Constrained Graph Variational Autoencoders for Molecule Design Qi Liu∗1, Miltiadis Allamanis2, Marc Brockschmidt2, and Alexander L. Gaunt2 1Singapore University of Technology and Design 2Microsoft Research, Cambridge qiliu@u.nus.edu, {miallama, mabrocks, algaunt}@microsoft.com Abstract Graphs are ubiquito...	2018	753
7,978	Hardware Conditioned Policies for Multi-Robot Transfer Learning Tao Chen The Robotics Institute Carnegie Mellon University Pittsburgh, PA 15213 taoc1@cs.cmu.edu Adithyavairavan Murali The Robotics Institute Carnegie Mellon University Pittsburgh, PA 15213 amurali@cs.cmu.edu Abhinav Gupta The Ro...	2018	754
7,979	Learning without the Phase: Regularized PhaseMax Achieves Optimal Sample Complexity Fariborz Salehi Department of Electrical Engineering Caltech fsalehi@caltech.edu Ehsan Abbasi Department of Electrical Engineering Caltech eabbasi@caltech.edu Babak Hassibi Department of Electrical Engineering Ca...	2018	755
7,980	Learning Disentangled Joint Continuous and Discrete Representations Emilien Dupont Schlumberger Software Technology Innovation Center Menlo Park, CA, USA dupont@slb.com Abstract We present a framework for learning disentangled and interpretable jointly continuous and discrete representations in an unsuper...	2018	756
7,981	Attacks Meet Interpretability: Attribute-steered Detection of Adversarial Samples Guanhong Tao∗, Shiqing Ma∗, Yingqi Liu, Xiangyu Zhang Department of Computer Science, Purdue University {taog, ma229, liu1751, xyzhang}@cs.purdue.edu Abstract Adversarial sample attacks perturb benign inputs to induce DNN misb...	2018	757
7,982	Learning To Learn Around A Common Mean Giulia Denevi1,2, Carlo Ciliberto3,4, Dimitris Stamos4 and Massimiliano Pontil1,4 1Istituto Italiano di Tecnologia (Italy), 2University of Genoa (Italy), 3Imperial College of London (UK), 4University College of London (UK) Abstract The problem of learning-to-learn (LTL) ...	2018	758
7,983	Recurrent Relational Networks Rasmus Berg Palm Technical University of Denmark Tradeshift rapal@dtu.dk Ulrich Paquet DeepMind upaq@google.com Ole Winther Technical University of Denmark olwi@dtu.dk Abstract This paper is concerned with learning to solve tasks that require a chain of interdepende...	2018	759
7,984	Bayesian Structure Learning by Recursive Bootstrap Raanan Y. Rohekar∗ Intel AI Lab raanan.yehezkel@intel.com Yaniv Gurwicz∗ Intel AI Lab yaniv.gurwicz@intel.com Shami Nisimov∗ Intel AI Lab shami.nisimov@intel.com Guy Koren Intel AI Lab guy.koren@intel.com Gal Novik Intel AI Lab gal.novik@i...	2018	76
7,985	Experimental Design for Cost-Aware Learning of Causal Graphs Erik M. Lindgren University of Texas at Austin erikml@utexas.edu Murat Kocaoglu MIT-IBM Watson AI Lab murat@ibm.com Alexandros G. Dimakis University of Texas at Austin dimakis@austin.utexas.edu Sriram Vishwanath University of Texas at ...	2018	760
7,986	Reinforcement Learning with Multiple Experts: A Bayesian Model Combination Approach Michael Gimelfarb Mechanical and Industrial Engineering University of Toronto mike.gimelfarb@mail.utoronto.ca Scott Sanner Mechanical and Industrial Engineering University of Toronto ssanner@mie.utoronto.ca Chi-Guhn ...	2018	761
7,987	Differentiable MPC for End-to-end Planning and Control Brandon Amos1 Ivan Dario Jimenez Rodriguez2 Jacob Sacks2 Byron Boots2 J. Zico Kolter13 1Carnegie Mellon University 2Georgia Tech 3Bosch Center for AI Abstract We present foundations for using Model Predictive Control (MPC) as a differentiable po...	2018	762
7,988	Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization Sijia Liu1 Bhavya Kailkhura2 Pin-Yu Chen1 Paishun Ting3 Shiyu Chang1 Lisa Amini1 1MIT-IBM Watson AI Lab, IBM Research 2Lawrence Livermore National Laboratory 3University of Michigan, Ann Arbor Abstract As application demands f...	2018	763
7,989	Near-Optimal Time and Sample Complexities for Solving Markov Decision Processes with a Generative Model Aaron Sidford Stanford University sidford@stanford.edu Mengdi Wang Princeton University mengdiw@princeton.edu Xian Wu Stanford University xwu20@stanford.edu Lin F. Yang Princeton University ...	2018	764
7,990	Algebraic tests of general Gaussian latent tree models Dennis Leung Department of Data Sciences and Operations University of Southern California dmhleung@uw.edu Mathias Drton Department of Statistics, University of Washington & Department of Mathematical Sciences, University of Copenhagen md5@uw.edu A...	2018	765
7,991	Binary Classiﬁcation from Positive-Conﬁdence Data Takashi Ishida1,2 Gang Niu2 Masashi Sugiyama2,1 1 The University of Tokyo, Tokyo, Japan 2 RIKEN, Tokyo, Japan {ishida@ms., sugi@}k.u-tokyo.ac.jp, gang.niu@riken.jp Abstract Can we learn a binary classiﬁer from only positive data, without any negative dat...	2018	766
7,992	Transfer Learning with Neural AutoML Catherine Wong MIT catwong@mit.edu Neil Houlsby Google Brain neilhoulsby@google.com Yifeng Lu Google Brain yifenglu@google.com Andrea Gesmundo Google Brain agesmundo@google.com Abstract We reduce the computational cost of Neural AutoML with transfer learn...	2018	767
7,993	Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs Timur Garipov∗1,2 Pavel Izmailov∗3 Dmitrii Podoprikhin∗4 Dmitry Vetrov5 Andrew Gordon Wilson3 1Samsung AI Center in Moscow, 2Skolkovo Institute of Science and Technology, 3Cornell University, 4Samsung-HSE Laboratory, National Research Unive...	2018	768
7,994	Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making Hoda Heidari ETH Zürich hheidari@inf.ethz.ch Claudio Ferrari ETH Zürich ferraric@ethz.ch Krishna P. Gummadi MPI-SWS gummadi@mpi-sws.org Andreas Krause ETH Zürich krausea@ethz.ch Abstract We draw attention...	2018	769
7,995	Efﬁcient Convex Completion of Coupled Tensors using Coupled Nuclear Norms Kishan Wimalawarne1 and Hiroshi Mamitsuka1,2 1Bioinformatics Center, Kyoto University, Kyoto, Japan 2Department of Computer Science, Aalto University, Espoo, Finland kishanwn@gmail.com, mami@kuicr.kyoto-u.ac.jp Abstract Coupled norm...	2018	77
7,996	A Uniﬁed View of Piecewise Linear Neural Network Veriﬁcation Rudy Bunel University of Oxford rudy@robots.ox.ac.uk Ilker Turkaslan University of Oxford ilker.turkaslan@lmh.ox.ac.uk Philip H.S. Torr University of Oxford philip.torr@eng.ox.ac.uk Pushmeet Kohli Deepmind pushmeet@google.com M. Pawa...	2018	770
7,997	Lifted Weighted Mini-Bucket Nicholas Gallo University of California Irvine Irvine, CA 92637-3435 ngallo1@uci.edu Alexander Ihler University of California Irvine Irvine, CA 92637-3435 ihler@ics.uci.edu Abstract Many graphical models, such as Markov Logic Networks (MLNs) with evidence, possess highl...	2018	771
7,998	Can We Gain More from Orthogonality Regularizations in Training Deep CNNs? Nitin Bansal Xiaohan Chen Zhangyang Wang Department of Computer Science and Engineering Texas A&M University, College Station, TX 77843, USA {bansa01, chernxh, atlaswang}@tamu.edu Abstract This paper seeks to answer the quest...	2018	772
7,999	Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners Yuxin Chen† Adish Singla‡ Oisin Mac Aodha† Pietro Perona† Yisong Yue† †Caltech, {chenyux, macaodha, perona, yyue}@caltech.edu, ‡MPI-SWS, adishs@mpi-sws.org Abstract In real-world applications of education, a...	2018	773

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