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NIPS · 24.8k rows

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6,700	Deep Hyperspherical Learning Weiyang Liu1, Yan-Ming Zhang2, Xingguo Li3,1, Zhiding Yu4, Bo Dai1, Tuo Zhao1, Le Song1 1Georgia Institute of Technology 2Institute of Automation, Chinese Academy of Sciences 3University of Minnesota 4Carnegie Mellon University {wyliu,tourzhao}@gatech.edu, ymzhang@nlpr.ia.ac.cn,...	2017	223
6,701	Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts Raymond A. Yeh, Jinjun Xiong†, Wen-mei W. Hwu, Minh N. Do, Alexander G. Schwing Department of Electrical Engineering, University of Illinois at Urbana-Champaign †IBM Thomas J. Watson Research Center yeh17@illinois...	2017	224
6,702	Off-policy evaluation for slate recommendation Adith Swaminathan Microsoft Research, Redmond adswamin@microsoft.com Akshay Krishnamurthy University of Massachusetts, Amherst akshay@cs.umass.edu Alekh Agarwal Microsoft Research, New York alekha@microsoft.com Miroslav Dudík Microsoft Research, New Y...	2017	225
6,703	Unbiased estimates for linear regression via volume sampling Michał Derezi´nski Department of Computer Science University of California Santa Cruz mderezin@ucsc.edu Manfred K. Warmuth Department of Computer Science University of California Santa Cruz manfred@ucsc.edu Abstract Given a full rank mat...	2017	226
6,704	Revisiting Perceptron: Efﬁcient and Label-Optimal Learning of Halfspaces Songbai Yan UC San Diego La Jolla, CA yansongbai@ucsd.edu Chicheng Zhang∗ Microsoft Research New York, NY chicheng.zhang@microsoft.com Abstract It has been a long-standing problem to efﬁciently learn a halfspace using as few ...	2017	227
6,705	Rényi Differential Privacy Mechanisms for Posterior Sampling Joseph Geumlek University of California, San Diego jgeumlek@cs.ucsd.edu Shuang Song University of California, San Diego shs037@eng.ucsd.edu Kamalika Chaudhuri University of California, San Diego kamalika@cs.ucsd.edu Abstract With the n...	2017	228
6,706	Variable Importance using Decision Trees S. Jalil Kazemitabar UCLA sjalilk@ucla.edu Arash A. Amini UCLA aaamini@ucla.edu Adam Bloniarz UC Berkeley∗ adam@stat.berkeley.edu Ameet Talwalkar CMU talwalkar@cmu.edu Abstract Decision trees and random forests are well established models that not onl...	2017	229
6,707	Minimax Estimation of Bandable Precision Matrices Addison J. Hu∗ Department of Statistics and Data Science Yale University New Haven, CT 06520 addison.hu@yale.edu Sahand N. Negahban Department of Statistics and Data Science Yale University New Haven, CT 06520 sahand.negahban@yale.edu Abstract Th...	2017	23
6,708	A simple model of recognition and recall memory Nisheeth Srivastava Computer Science, IIT Kanpur Kanpur, UP 208016 nsrivast@cse.iitk.ac.in Edward Vul Dept of Psychology, UCSD 9500 Gilman Drive La Jolla CA 92093 evul@ucsd.edu Abstract We show that several striking differences in memory performance be...	2017	230
6,709	Implicit Regularization in Matrix Factorization Suriya Gunasekar TTI at Chicago suriya@ttic.edu Blake Woodworth TTI at Chicago blake@ttic.edu Srinadh Bhojanapalli TTI at Chicago srinadh@ttic.edu Behnam Neyshabur TTI at Chicago behnam@ttic.edu Nathan Srebro TTI at Chicago nati@ttic.edu Ab...	2017	231
6,710	Continuous DR-submodular Maximization: Structure and Algorithms An Bian ETH Zurich ybian@inf.ethz.ch Kﬁr Y. Levy ETH Zurich yehuda.levy@inf.ethz.ch Andreas Krause ETH Zurich krausea@ethz.ch Joachim M. Buhmann ETH Zurich jbuhmann@inf.ethz.ch Abstract DR-submodular continuous functions are i...	2017	232
6,711	Decoupling “when to update” from “how to update” Eran Malach School of Computer Science The Hebrew University, Israel eran.malach@mail.huji.ac.il Shai Shalev-Shwartz School of Computer Science The Hebrew University, Israel shais@cs.huji.ac.il Abstract Deep learning requires data. A useful approach t...	2017	233
6,712	Regret Analysis for Continuous Dueling Bandit Wataru Kumagai Center for Advanced Intelligence Project RIKEN 1-4-1, Nihonbashi, Chuo, Tokyo 103-0027, Japan wataru.kumagai@riken.jp Abstract The dueling bandit is a learning framework wherein the feedback information in the learning process is restricted to...	2017	234
6,713	One-Sided Unsupervised Domain Mapping Sagie Benaim1 and Lior Wolf1,2 1The Blavatnik School of Computer Science , Tel Aviv University, Israel 2Facebook AI Research Abstract In unsupervised domain mapping, the learner is given two unmatched datasets A and B. The goal is to learn a mapping GAB that translates ...	2017	235
6,714	Poincaré Embeddings for Learning Hierarchical Representations Maximilian Nickel Facebook AI Research maxn@fb.com Douwe Kiela Facebook AI Research dkiela@fb.com Abstract Representation learning has become an invaluable approach for learning from symbolic data such as text and graphs. However, state-of-...	2017	236
6,715	Variance-based Regularization with Convex Objectives Hongseok Namkoong Stanford University hnamk@stanford.edu John C. Duchi Stanford University jduchi@stanford.edu Abstract We develop an approach to risk minimization and stochastic optimization that provides a convex surrogate for variance, allowing n...	2017	237
6,716	A Sharp Error Analysis for the Fused Lasso, with Application to Approximate Changepoint Screening Kevin Lin Carnegie Mellon University Pittsburgh, PA 15213 kevinl1@andrew.cmu.edu James Sharpnack University of California, Davis Davis, CA 95616 jsharpna@ucdavis.edu Alessandro Rinaldo Carnegie Mellon...	2017	238
6,717	Cross-Spectral Factor Analysis Neil M. Gallagher1,, Kyle Ulrich2,, Austin Talbot3, Kafui Dzirasa1,4, Lawrence Carin2 and David E. Carlson5,6 1Department of Neurobiology, 2Department of Electrical and Computer Engineering, 3Department of Statistical Science, 4Department of Psychiatry and Behavioral Sciences, 5...	2017	239
6,718	Kernel functions based on triplet comparisons Matthäus Kleindessner⇤ Department of Computer Science Rutgers University Piscataway, NJ 08854 mk1572@cs.rutgers.edu Ulrike von Luxburg Department of Computer Science University of Tübingen Max Planck Institute for Intelligent Systems, Tübingen luxburg@in...	2017	24
6,719	Self-Normalizing Neural Networks Günter Klambauer Thomas Unterthiner Andreas Mayr Sepp Hochreiter LIT AI Lab & Institute of Bioinformatics, Johannes Kepler University Linz A-4040 Linz, Austria {klambauer,unterthiner,mayr,hochreit}@bioinf.jku.at Abstract Deep Learning has revolutionized vision via co...	2017	240
6,720	Fast amortized inference of neural activity from calcium imaging data with variational autoencoders Artur Speiser12, Jinyao Yan3, Evan Archer4∗, Lars Buesing4†, Srinivas C. Turaga3‡ and Jakob H. Macke1‡§ 1research center caesar, an associate of the Max Planck Society, Bonn, Germany 2IMPRS Brain and Behavior B...	2017	241
6,721	Asynchronous Parallel Coordinate Minimization for MAP Inference Ofer Meshi Google meshi@google.com Alexander G. Schwing Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign aschwing@illinois.edu Abstract Finding the maximum a-posteriori (MAP) assignment is a c...	2017	242
6,722	Inductive Representation Learning on Large Graphs William L. Hamilton∗ wleif@stanford.edu Rex Ying∗ rexying@stanford.edu Jure Leskovec jure@cs.stanford.edu Department of Computer Science Stanford University Stanford, CA, 94305 Abstract Low-dimensional embeddings of nodes in large graphs have prove...	2017	243
6,723	Data-Efﬁcient Reinforcement Learning in Continuous State-Action Gaussian-POMDPs Rowan Thomas McAllister Department of Engineering Cambridge University Cambridge, CB2 1PZ rtm26@cam.ac.uk Carl Edward Rasmussen Department of Engineering University of Cambridge Cambridge, CB2 1PZ cer54@cam.ac.uk Abs...	2017	244
6,724	Coded Distributed Computing for Inverse Problems Yaoqing Yang, Pulkit Grover and Soummya Kar Carnegie Mellon University {yyaoqing, pgrover, soummyak}@andrew.cmu.edu Abstract Computationally intensive distributed and parallel computing is often bottlenecked by a small set of slow workers known as stragglers....	2017	245
6,725	Dykstra’s Algorithm, ADMM, and Coordinate Descent: Connections, Insights, and Extensions Ryan J. Tibshirani Department of Statistics and Machine Learning Department Carnegie Mellon University Pittsburgh, PA 15213 ryantibs@stat.cmu.edu Abstract We study connections between Dykstra’s algorithm for project...	2017	246
6,726	Training recurrent networks to generate hypotheses about how the brain solves hard navigation problems Ingmar Kanitscheider & Ila Fiete Department of Neuroscience The University of Texas Austin, TX 78712 ikanitscheider, ilafiete @mail.clm.utexas.edu Abstract Self-localization during navigation with nois...	2017	247
6,727	SafetyNets: Veriﬁable Execution of Deep Neural Networks on an Untrusted Cloud Zahra Ghodsi, Tianyu Gu, Siddharth Garg New York University {zg451, tg1553, sg175}@nyu.edu Abstract Inference using deep neural networks is often outsourced to the cloud since it is a computationally demanding task. However, thi...	2017	248
6,728	Improved Graph Laplacian via Geometric Consistency Dominique C. Perrault-Joncas Google, Inc. dominiquep@google.com Marina Meil˘a Department of Statistics University of Washington mmp2@uw.edu James McQueen Amazon jmcq@amazon.com Abstract In all manifold learning algorithms and tasks setting the...	2017	249
6,729	Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization Fabian Pedregosa INRIA/ENS∗ Paris, France R´emi Leblond INRIA/ENS∗ Paris, France Simon Lacoste-Julien MILA and DIRO Universit´e de Montr´eal, Canada Abstract Due to their simplicity and excellent performance, p...	2017	25
6,730	Generalization Properties of Learning with Random Features Alessandro Rudi ∗ INRIA - Sierra Project-team, ´Ecole Normale Sup´erieure, Paris, 75012 Paris, France alessandro.rudi@inria.fr Lorenzo Rosasco University of Genova, Istituto Italiano di Tecnologia, Massachusetts Institute of Technology. lr...	2017	250
6,731	Predictive-State Decoders: Encoding the Future into Recurrent Networks Arun Venkatraman1∗, Nicholas Rhinehart1∗, Wen Sun1, Lerrel Pinto1, Martial Hebert1, Byron Boots2, Kris M. Kitani1, J. Andrew Bagnell1 1The Robotics Institute, Carnegie-Mellon University, Pittsburgh, PA 2School of Interactive Computing, Geo...	2017	251
6,732	Federated Multi-Task Learning Virginia Smith Stanford smithv@stanford.edu Chao-Kai Chiang∗ USC chaokaic@usc.edu Maziar Sanjabi∗ USC maziarsanjabi@gmail.com Ameet Talwalkar CMU talwalkar@cmu.edu Abstract Federated learning poses new statistical and systems challenges in training machine lea...	2017	252
6,733	Learning Causal Structures Using Regression Invariance AmirEmad Ghassami⇤†, Saber Salehkaleybar†, Negar Kiyavash⇤†, Kun Zhang‡ ⇤Department of ECE, University of Illinois at Urbana-Champaign, Urbana, USA. †Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Urbana, USA. ‡Department of P...	2017	253
6,734	Practical Hash Functions for Similarity Estimation and Dimensionality Reduction Søren Dahlgaard University of Copenhagen / SupWiz s.dahlgaard@supwiz.com Mathias Bæk Tejs Knudsen University of Copenhagen / SupWiz m.knudsen@supwiz.com Mikkel Thorup University of Copenhagen mthorup@di.ku.dk Abstract ...	2017	254
6,735	Gaussian Quadrature for Kernel Features Tri Dao Department of Computer Science Stanford University Stanford, CA 94305 trid@stanford.edu Christopher De Sa Department of Computer Science Cornell University Ithaca, NY 14853 cdesa@cs.cornell.edu Christopher Ré Department of Computer Science Stanfo...	2017	255
6,736	Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial Nets Karol Hausman∗†, Yevgen Chebotar∗†‡, Stefan Schaal†‡, Gaurav Sukhatme†, Joseph J. Lim† †University of Southern California, Los Angeles, CA, USA ‡Max-Planck-Institute for Intelligent Systems, Tübingen, Germany {ha...	2017	256
6,737	Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees Francesco Locatello MPI for Intelligent Systems - ETH Zurich locatelf@ethz.ch Michael Tschannen ETH Zurich michaelt@nari.ee.ethz.ch Gunnar Rätsch ETH Zurich raetsch@inf.ethz.ch Martin Jaggi EPFL martin.jaggi@epfl.c...	2017	257
6,738	On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks Arturs Backurs CSAIL MIT backurs@mit.edu Piotr Indyk CSAIL MIT indyk@mit.edu Ludwig Schmidt CSAIL MIT ludwigs@mit.edu Abstract Empirical risk minimization (ERM) is ubiquitous in machine lear...	2017	258
6,739	Acceleration and Averaging In Stochastic Descent Dynamics Walid Krichene Google, Inc. walidk@google.com Peter Bartlett U.C. Berkeley bartlett@cs.berkeley.edu Abstract We formulate and study a general family of (continuous-time) stochastic dynamics for accelerated ﬁrst-order minimization of smooth co...	2017	259
6,740	A New Theory for Matrix Completion Guangcan Liu∗ Qingshan Liu† Xiao-Tong Yuan‡ B-DAT, School of Information & Control, Nanjing Univ Informat Sci & Technol NO 219 Ningliu Road, Nanjing, Jiangsu, China, 210044 {gcliu,qsliu,xtyuan}@nuist.edu.cn Abstract Prevalent matrix completion theories reply on an assu...	2017	26
6,741	LightGBM: A Highly Efﬁcient Gradient Boosting Decision Tree Guolin Ke1, Qi Meng2, Thomas Finley3, Taifeng Wang1, Wei Chen1, Weidong Ma1, Qiwei Ye1, Tie-Yan Liu1 1Microsoft Research 2Peking University 3 Microsoft Redmond 1{guolin.ke, taifengw, wche, weima, qiwye, tie-yan.liu}@microsoft.com; 2qimeng13@pku...	2017	260
6,742	The Neural Hawkes Process: A Neurally Self-Modulating Multivariate Point Process Hongyuan Mei Jason Eisner Department of Computer Science, Johns Hopkins University 3400 N. Charles Street, Baltimore, MD 21218 U.S.A {hmei,jason}@cs.jhu.edu Abstract Many events occur in the world. Some event types are stoc...	2017	261
6,743	Bayesian Optimization with Gradients Jian Wu 1 Matthias Poloczek 2 Andrew Gordon Wilson 1 Peter I. Frazier 1 1 Cornell University, 2 University of Arizona Abstract Bayesian optimization has been successful at global optimization of expensiveto-evaluate multimodal objective functions. However, unlike most ...	2017	262
6,744	Visual Reference Resolution using Attention Memory for Visual Dialog Paul Hongsuck Seo† Andreas Lehrmann§ Bohyung Han† Leonid Sigal§ †POSTECH §Disney Research {hsseo, bhhan}@postech.ac.kr {andreas.lehrmann, lsigal}@disneyresearch.com Abstract Visual dialog is a task of answering a series of inter-de...	2017	263
6,745	Straggler Mitigation in Distributed Optimization Through Data Encoding Can Karakus UCLA Los Angeles, CA karakus@ucla.edu Yifan Sun Technicolor Research Los Altos, CA Yifan.Sun@technicolor.com Suhas Diggavi UCLA Los Angeles, CA suhasdiggavi@ucla.edu Wotao Yin UCLA Los Angeles, CA wotaoy...	2017	264
6,746	Using Options and Covariance Testing for Long Horizon Off-Policy Policy Evaluation Zhaohan Daniel Guo Carnegie Mellon University Pittsburgh, PA 15213 zguo@cs.cmu.edu Philip S. Thomas University of Massachusetts Amherst Amherst, MA 01003 pthomas@cs.umass.edu Emma Brunskill Stanford University Sta...	2017	265
6,747	Attentional Pooling for Action Recognition Rohit Girdhar Deva Ramanan The Robotics Institute, Carnegie Mellon University http://rohitgirdhar.github.io/AttentionalPoolingAction Abstract We introduce a simple yet surprisingly powerful model to incorporate attention in action recognition and human object int...	2017	266
6,748	Testing and Learning on Distributions with Symmetric Noise Invariance Ho Chung Leon Law Department of Statistics University Of Oxford hlaw@stats.ox.ac.uk Christopher Yau Centre for Computational Biology University of Birmingham c.yau@bham.ac.uk Dino Sejdinovic Department of Statistics University...	2017	267
6,749	Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results Antti Tarvainen The Curious AI Company tarvaina@cai.fi Harri Valpola The Curious AI Company harri@cai.fi Abstract The recently proposed Temporal Ensembling has achieved state-of-th...	2017	268
6,750	Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments Ryan Lowe∗ McGill University OpenAI Yi Wu∗ UC Berkeley Aviv Tamar UC Berkeley Jean Harb McGill University OpenAI Pieter Abbeel UC Berkeley OpenAI Igor Mordatch OpenAI Abstract We explore deep reinforcement learni...	2017	269
6,751	A Bayesian Data Augmentation Approach for Learning Deep Models Toan Tran1, Trung Pham1, Gustavo Carneiro1, Lyle Palmer2 and Ian Reid1 1School of Computer Science, 2School of Public Health The University of Adelaide, Australia {toan.m.tran, trung.pham, gustavo.carneiro, lyle.palmer, ian.reid} @adelaide.edu.a...	2017	27
6,752	Log-normality and Skewness of Estimated State/Action Values in Reinforcement Learning Liangpeng Zhang1,2, Ke Tang3,1, and Xin Yao3,2 1School of Computer Science and Technology, University of Science and Technology of China 2University of Birmingham, U.K. 3Shenzhen Key Lab of Computational Intelligence, De...	2017	270
6,753	Bayesian Compression for Deep Learning Christos Louizos University of Amsterdam TNO Intelligent Imaging c.louizos@uva.nl Karen Ullrich University of Amsterdam k.ullrich@uva.nl Max Welling University of Amsterdam CIFAR∗ m.welling@uva.nl Abstract Compression and computational efﬁciency in deep l...	2017	271
6,754	Is Input Sparsity Time Possible for Kernel Low-Rank Approximation? Cameron Musco MIT cnmusco@mit.edu David P. Woodruff Carnegie Mellon University dwoodruf@cs.cmu.edu Abstract Low-rank approximation is a common tool used to accelerate kernel methods: the n⇥n kernel matrix K is approximated via a rank...	2017	272
6,755	Convergent Block Coordinate Descent for Training Tikhonov Regularized Deep Neural Networks Ziming Zhang and Matthew Brand Mitsubishi Electric Research Laboratories (MERL) Cambridge, MA 02139-1955 {zzhang, brand}@merl.com Abstract By lifting the ReLU function into a higher dimensional space, we develop a s...	2017	273
6,756	Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes Ahmed M. Alaa Electrical Engineering Department University of California, Los Angeles ahmedmalaa@ucla.edu Mihaela van der Schaar Department of Engineering Science University of Oxford mihaela.vanderschaar@eng.ox...	2017	274
6,757	Learning Overcomplete HMMs Vatsal Sharan Stanford University vsharan@stanford.edu Sham Kakade University of Washington sham@cs.washington.edu Percy Liang Stanford University pliang@cs.stanford.edu Gregory Valiant Stanford University valiant@stanford.edu Abstract We study the problem of learn...	2017	275
6,758	Convolutional Phase Retrieval Qing Qu Columbia University qq2105@columbia.edu Yuqian Zhang Columbia University yz2409@columbia.edu Yonina C. Eldar Technion yonina@ee.technion.ac.il John Wright Columbia University jw2966@columbia.edu Abstract We study the convolutional phase retrieval problem...	2017	276
6,759	Stochastic and Adversarial Online Learning without Hyperparameters Ashok Cutkosky Department of Computer Science Stanford University ashokc@cs.stanford.edu Kwabena Boahen Department of Bioengineering Stanford University boahen@stanford.edu Abstract Most online optimization algorithms focus on one ...	2017	277
6,760	Masked Autoregressive Flow for Density Estimation George Papamakarios University of Edinburgh g.papamakarios@ed.ac.uk Theo Pavlakou University of Edinburgh theo.pavlakou@ed.ac.uk Iain Murray University of Edinburgh i.murray@ed.ac.uk Abstract Autoregressive models are among the best performing neur...	2017	278
6,761	QSGD: Communication-Efﬁcient SGD via Gradient Quantization and Encoding Dan Alistarh IST Austria & ETH Zurich dan.alistarh@ist.ac.at Demjan Grubic ETH Zurich & Google demjangrubic@gmail.com Jerry Z. Li MIT jerryzli@mit.edu Ryota Tomioka Microsoft Research ryoto@microsoft.com Milan Vojnovic ...	2017	279
6,762	Deep Hyperalignment Muhammad Yousefnezhad, Daoqiang Zhang College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics {myousefnezhad,dqzhang}@nuaa.edu.cn Abstract This paper proposes Deep Hyperalignment (DHA) as a regularized, deep extension, scalable Hyperalignment (HA) ...	2017	28
6,763	Learning Hierarchical Information Flow with Recurrent Neural Modules Danijar Hafner ∗ Google Brain mail@danijar.com Alex Irpan Google Brain alexirpan@google.com James Davidson Google Brain jcdavidson@google.com Nicolas Heess Google DeepMind heess@google.com Abstract We propose ThalNet, a d...	2017	280
6,764	Deanonymization in the Bitcoin P2P Network Giulia Fanti and Pramod Viswanath Abstract Recent attacks on Bitcoin’s peer-to-peer (P2P) network demonstrated that its transaction-ﬂooding protocols, which are used to ensure network consistency, may enable user deanonymization—the linkage of a user’s IP address wit...	2017	281
6,765	Learning with Average Top-k Loss Yanbo Fan3,4,1 , Siwei Lyu1∗, Yiming Ying2 , Bao-Gang Hu3,4 1Department of Computer Science, University at Albany, SUNY 2Department of Mathematics and Statistics, University at Albany, SUNY 3National Laboratory of Pattern Recognition, CASIA 4University of Chinese Academy of Sc...	2017	282
6,766	MaskRNN: Instance Level Video Object Segmentation Yuan-Ting Hu UIUC ythu2@illinois.edu Jia-Bin Huang Virginia Tech jbhuang@vt.edu Alexander G. Schwing UIUC aschwing@illinois.edu Abstract Instance level video object segmentation is an important technique for video editing and compression. To ca...	2017	283
6,767	Max-Margin Invariant Features from Transformed Unlabeled Data Dipan K. Pal, Ashwin A. Kannan∗, Gautam Arakalgud∗, Marios Savvides Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh, PA 15213 {dipanp,aalapakk,garakalgud,marioss}@cmu.edu Abstract The study of represent...	2017	284
6,768	Sparse Approximate Conic Hulls Gregory Van Buskirk, Benjamin Raichel, and Nicholas Ruozzi Department of Computer Science University of Texas at Dallas Richardson, TX 75080 {greg.vanbuskirk, benjamin.raichel, nicholas.ruozzi}@utdallas.edu Abstract We consider the problem of computing a restricted nonnegati...	2017	285
6,769	Label Distribution Learning Forests Wei Shen1,2, Kai Zhao1, Yilu Guo1, Alan Yuille2 1 Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Shanghai Institute for Advanced Communication and Data Science, School of Communication and Information Engineering, Shanghai University 2 Department of C...	2017	286
6,770	Efﬁcient Sublinear-Regret Algorithms for Online Sparse Linear Regression with Limited Observation Shinji Ito NEC Corporation s-ito@me.jp.nec.com Daisuke Hatano National Institute of Informatics hatano@nii.ac.jp Hanna Sumita National Institute of Informatics sumita@nii.ac.jp Akihiro Yabe NEC Corp...	2017	287
6,771	Accelerated First-order Methods for Geodesically Convex Optimization on Riemannian Manifolds Yuanyuan Liu1, Fanhua Shang1∗, James Cheng1, Hong Cheng2, Licheng Jiao3 1Dept. of Computer Science and Engineering, The Chinese University of Hong Kong 2Dept. of Systems Engineering and Engineering Management, The Chi...	2017	288
6,772	Hierarchical Implicit Models and Likelihood-Free Variational Inference Dustin Tran Columbia University Rajesh Ranganath Princeton University David M. Blei Columbia University Abstract Implicit probabilistic models are a ﬂexible class of models deﬁned by a simulation process for data. They form the bas...	2017	289
6,773	Best of Both Worlds: Transferring Knowledge from Discriminative Learning to a Generative Visual Dialog Model Jiasen Lu1∗, Anitha Kannan2∗, Jianwei Yang1, Devi Parikh3,1, Dhruv Batra3,1 1 Georgia Institute of Technology, 2 Curai, 3 Facebook AI Research {jiasenlu, jw2yang, parikh, dbatra}@gatech.edu Abstract ...	2017	29
6,774	Learning the Morphology of Brain Signals Using Alpha-Stable Convolutional Sparse Coding Mainak Jas1, Tom Dupré La Tour1, Umut ¸Sim¸sekli1, Alexandre Gramfort1,2 1: LTCI, Telecom ParisTech, Université Paris-Saclay, Paris, France 2: INRIA, Université Paris-Saclay, Saclay, France Abstract Neural time-series da...	2017	290
6,775	Modulating early visual processing by language Harm de Vries∗ University of Montreal mail@harmdevries.com Florian Strub∗ Univ. Lille, CNRS, Centrale Lille, Inria, UMR 9189 CRIStAL florian.strub@inria.fr Jérémie Mary† Univ. Lille, CNRS, Centrale Lille, Inria, UMR 9189 CRIStAL jeremie.mary@univ-lill...	2017	291
6,776	Discriminative State-Space Models Vitaly Kuznetsov Google Research New York, NY 10011, USA vitaly@cims.nyu.edu Mehryar Mohri Courant Institute and Google Research New York, NY 10011, USA mohri@cims.nyu.edu Abstract We introduce and analyze Discriminative State-Space Models for forecasting nonstation...	2017	292
6,777	Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols Serhii Havrylov ILCC, School of Informatics University of Edinburgh s.havrylov@inf.ed.ac.uk Ivan Titov ILCC, School of Informatics University of Edinburgh ILLC, University of Amsterdam ititov@inf.ed.ac.uk...	2017	293
6,778	Wider and Deeper, Cheaper and Faster: Tensorized LSTMs for Sequence Learning Zhen He1,2, Shaobing Gao3, Liang Xiao2, Daxue Liu2, Hangen He2, and David Barber ∗ 1,4 1University College London, 2National University of Defense Technology, 3Sichuan University, 4Alan Turing Institute Abstract Long Short-Term...	2017	294
6,779	Online Inﬂuence Maximization under Independent Cascade Model with Semi-Bandit Feedback Zheng Wen Adobe Research zwen@adobe.com Branislav Kveton Adobe Research kveton@adobe.com Michal Valko SequeL team, INRIA Lille - Nord Europe michal.valko@inria.fr Sharan Vaswani University of British Columbia ...	2017	295
6,780	Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization Ahmet Alacaoglu1 Quoc Tran-Dinh2 Olivier Fercoq3 Volkan Cevher1 1Laboratory for Information and Inference Systems (LIONS), EPFL, Lausanne, Switzerland {ahmet.alacaoglu, volkan.cevher}@epfl.ch 2 Department of Statistics an...	2017	296
6,781	Linearly constrained Gaussian processes Carl Jidling Department of Information Technology Uppsala University, Sweden carl.jidling@it.uu.se Niklas Wahlström Department of Information Technology Uppsala University, Sweden niklas.wahlstrom@it.uu.se Adrian Wills School of Engineering University of New...	2017	297
6,782	Solid Harmonic Wavelet Scattering: Predicting Quantum Molecular Energy from Invariant Descriptors of 3D Electronic Densities Michael Eickenberg Department of computer science Ecole normale supérieure PSL Research University, 75005 Paris, France michael.eickenberg@nsup.org Georgios Exarchakis Departmen...	2017	298
6,783	On Frank-Wolfe and Equilibrium Computation Jacob Abernethy Georgia Institute of Technology prof@gatech.edu Jun-Kun Wang Georgia Institute of Technology jimwang@gatech.edu Abstract We consider the Frank-Wolfe (FW) method for constrained convex optimization, and we show that this classical technique can...	2017	299
6,784	Learning A Structured Optimal Bipartite Graph for Co-Clustering Feiping Nie1, Xiaoqian Wang2, Cheng Deng3, Heng Huang2∗ 1 School of Computer Science, Center for OPTIMAL, Northwestern Polytechnical University, China 2 Department of Electrical and Computer Engineering, University of Pittsburgh, USA 3 School of ...	2017	3
6,785	PASS-GLM: polynomial approximate sufﬁcient statistics for scalable Bayesian GLM inference Jonathan H. Huggins CSAIL, MIT jhuggins@mit.edu Ryan P. Adams Google Brain and Princeton rpa@princeton.edu Tamara Broderick CSAIL, MIT tbroderick@csail.mit.edu Abstract Generalized linear models (GLMs)—such...	2017	30
6,786	Generalizing GANs: A Turing Perspective Roderich Groß and Yue Gu Department of Automatic Control and Systems Engineering The University of Shefﬁeld {r.gross,ygu16}@sheffield.ac.uk Wei Li Department of Electronics The University of York wei.li@york.ac.uk Melvin Gauci Wyss Institute for Biologically I...	2017	300
6,787	Predicting Scene Parsing and Motion Dynamics in the Future Xiaojie Jin1, Huaxin Xiao2, Xiaohui Shen3, Jimei Yang3, Zhe Lin3 Yunpeng Chen2, Zequn Jie4, Jiashi Feng2, Shuicheng Yan5,2 1NUS Graduate School for Integrative Science and Engineering (NGS), NUS 2Department of ECE, NUS 3Adobe Research 4Tencent AI ...	2017	301
6,788	A Screening Rule for ℓ1-Regularized Ising Model Estimation Zhaobin Kuang1, Sinong Geng2, David Page3 University of Wisconsin zkuang@wisc.edu1, sgeng2@wisc.edu2, page@biostat.wisc.edu3 Abstract We discover a screening rule for ℓ1-regularized Ising model estimation. The simple closed-form screening rule is ...	2017	302
6,789	A Minimax Optimal Algorithm for Crowdsourcing Thomas Bonald Telecom ParisTech thomas.bonald@telecom-paristech.fr Richard Combes Centrale-Supelec / L2S richard.combes@supelec.fr Abstract We consider the problem of accurately estimating the reliability of workers based on noisy labels they provide, whic...	2017	303
6,790	Communication-Efﬁcient Distributed Learning of Discrete Probability Distributions Ilias Diakonikolas CS, USC diakonik@usc.edu Elena Grigorescu CS, Purdue elena-g@purdue.edu Jerry Li EECS & CSAIL, MIT jerryzli@mit.edu Abhiram Natarajan CS, Purdue nataraj2@purdue.edu Krzysztof Onak IBM Resea...	2017	304
6,791	VAIN: Attentional Multi-agent Predictive Modeling Yedid Hoshen Facebook AI Research, NYC yedidh@fb.com Abstract Multi-agent predictive modeling is an essential step for understanding physical, social and team-play systems. Recently, Interaction Networks (INs) were proposed for the task of modeling multi-a...	2017	305
6,792	Hierarchical Attentive Recurrent Tracking Adam R. Kosiorek Department of Engineering Science University of Oxford adamk@robots.ox.ac.uk Alex Bewley Department of Engineering Science University of Oxford bewley@robots.ox.ac.uk Ingmar Posner Department of Engineering Science University of Oxford i...	2017	306
6,793	Sobolev Training for Neural Networks Wojciech Marian Czarnecki, Simon Osindero, Max Jaderberg Grzegorz Swirszcz, and Razvan Pascanu DeepMind, London, UK {lejlot,osindero,jaderberg,swirszcz,razp}@google.com Abstract At the heart of deep learning we aim to use neural networks as function approximators – train...	2017	307
6,794	Doubly Accelerated Stochastic Variance Reduced Dual Averaging Method for Regularized Empirical Risk Minimization Tomoya Murata NTT DATA Mathematical Systems Inc. , Tokyo, Japan murata@msi.co.jp Taiji Suzuki Department of Mathematical Informatics Graduate School of Information Science and Technology, The...	2017	308
6,795	Learning with Feature Evolvable Streams Bo-Jian Hou Lijun Zhang Zhi-Hua Zhou National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, 210023, China {houbj,zhanglj,zhouzh}@lamda.nju.edu.cn Abstract Learning with streaming data has attracted much attention during the past few ye...	2017	309
6,796	Online Multiclass Boosting Young Hun Jung Jack Goetz Department of Statistics University of Michigan Ann Arbor, MI 48109 {yhjung, jrgoetz, tewaria}@umich.edu Ambuj Tewari Abstract Recent work has extended the theoretical analysis of boosting algorithms to multiclass problems and to online settings. Ho...	2017	31
6,797	Safe Model-based Reinforcement Learning with Stability Guarantees Felix Berkenkamp Department of Computer Science ETH Zurich befelix@inf.ethz.ch Matteo Turchetta Department of Computer Science, ETH Zurich matteotu@inf.ethz.ch Angela P. Schoellig Institute for Aerospace Studies University of Toro...	2017	310
6,798	Time-dependent spatially varying graphical models, with application to brain fMRI data analysis Kristjan Greenewald Department of Statistics Harvard University Seyoung Park Department of Biostatistics Yale University Shuheng Zhou Department of Statistics University of Michigan Alexander Giessing ...	2017	311
6,799	Clone MCMC: Parallel High-Dimensional Gaussian Gibbs Sampling Andrei-Cristian B˘arbos IMS Laboratory Univ. Bordeaux - CNRS - BINP andbarbos@u-bordeaux.fr François Caron Department of Statistics University of Oxford caron@stats.ox.ac.uk Jean-François Giovannelli IMS Laboratory Univ. Bordeaux - CN...	2017	312

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