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NIPS · 24.8k rows

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8,100	Virtual Class Enhanced Discriminative Embedding Learning Binghui Chen1, Weihong Deng1, Haifeng Shen2 1Beijing University of Posts and Telecommunications 2AI Labs, Didi Chuxing, Beijing 100193, China chenbinghui@bupt.edu.cn, whdeng@bupt.edu.cn, shenhaifeng@didiglobal.com Abstract Recently, learning discrim...	2018	864
8,101	Neural Networks Trained to Solve Differential Equations Learn General Representations Martin Magill U. of Ontario Inst. of Tech. martin.magill1@uoit.net Faisal Z. Qureshi U. of Ontario Inst. of Tech. faisal.qureshi@uoit.ca Hendrick W. de Haan U. of Ontario Inst. of Tech. hendrick.dehaan@uoit.ca Ab...	2018	865
8,102	Deep Generative Models with Learnable Knowledge Constraints Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Xiaodan Liang, Lianhui Qin, Haoye Dong, Eric P. Xing Carnegie Mellon University, Petuum Inc. {zhitingh,zichaoy,rsalakhu,xiaodan1}@cs.cmu.edu, eric.xing@petuum.com Abstract The broad set of deep gener...	2018	866
8,103	How to Start Training: The Effect of Initialization and Architecture Boris Hanin Department of Mathematics Texas A& M University College Station, TX, USA bhanin@math.tamu.edu David Rolnick Department of Mathematics Massachusetts Institute of Technology Cambridge, MA, USA drolnick@mit.edu Abstrac...	2018	867
8,104	Video-to-Video Synthesis Ting-Chun Wang1, Ming-Yu Liu1, Jun-Yan Zhu2, Guilin Liu1, Andrew Tao1, Jan Kautz1, Bryan Catanzaro1 1NVIDIA, 2MIT CSAIL {tingchunw,mingyul,guilinl,atao,jkautz,bcatanzaro}@nvidia.com, junyanz@mit.edu Abstract We study the problem of video-to-video synthesis, whose goal is to learn ...	2018	868
8,105	Near-Optimal Policies for Dynamic Multinomial Logit Assortment Selection Models Yining Wang Machine Learning Department Carnegie Mellon University yiningwa@cs.cmu.edu Xi Chen Stern School of Business New York University xchen3@stern.nyu.edu Yuan Zhou Computer Science Department Indiana Universit...	2018	869
8,106	Which Neural Net Architectures Give Rise to Exploding and Vanishing Gradients? Boris Hanin Department of Mathematics Texas A& M University College Station, TX, USA bhanin@math.tamu.edu Abstract We give a rigorous analysis of the statistical behavior of gradients in a randomly initialized fully connect...	2018	87
8,107	Occam’s razor is insufﬁcient to infer the preferences of irrational agents S¨oren Mindermann ∗* † Vector Institute University of Toronto soeren.mindermann@gmail.com Stuart Armstrong* ‡ Future of Humanity Institute University of Oxford stuart.armstrong@philosophy.ox.ac.uk Abstract Inverse reinforce...	2018	870
8,108	Bandit Learning with Implicit Feedback Yi Qi1, Qingyun Wu2, Hongning Wang2, Jie Tang1, Maosong Sun1 1 State Key Lab of Intell. Tech. & Sys., Institution for Artiﬁcial Intelligence, Dept. of Comp. Sci. & Tech., Tsinghua University, Beijing, China 2 Department of Computer Science, University of Virginia qi-y1...	2018	871
8,109	Adversarial Regularizers in Inverse Problems Sebastian Lunz DAMTP University of Cambridge Cambridge CB3 0WA lunz@math.cam.ac.uk Ozan Öktem Department of Mathematics KTH - Royal Institute of Technology 100 44 Stockholm ozan@kth.se Carola-Bibiane Schönlieb DAMTP University of Cambridge Cambrid...	2018	872
8,110	The emergence of multiple retinal cell types through efﬁcient coding of natural movies Samuel A. Ocko⇤†, Jack Lindsey⇤, Surya Ganguli1, Stephane Deny† Department of Applied Physics, Stanford and 1Google Brain, Mountain View, CA Abstract One of the most striking aspects of early visual processing in the retina...	2018	873
8,111	Multiple Instance Learning for Efﬁcient Sequential Data Classiﬁcation on Resource-constrained Devices Don Kurian Dennis Chirag Pabbaraju Harsha Vardhan Simhadri Prateek Jain Microsoft Research, India {t-dodenn, t-chpab, harshasi, prajain}@microsoft.com Abstract We study the problem of fast and efﬁcien...	2018	874
8,112	Dropping Symmetry for Fast Symmetric Nonnegative Matrix Factorization Zhihui Zhu∗ Mathematical Institute for Data Science Johns Hopkins University Baltimore, MD, USA zzhu29@jhu.edu Xiao Li∗ Department of Electronic Engineering The Chinese University of Hong Kong Shatin, NT, Hong Kong xli@ee.cuhk.e...	2018	875
8,113	On the Local Minima of the Empirical Risk Chi Jin∗ University of California, Berkeley chijin@cs.berkeley.edu Lydia T. Liu∗ University of California, Berkeley lydiatliu@cs.berkeley.edu Rong Ge Duke University rongge@cs.duke.edu Michael I. Jordan University of California, Berkeley jordan@cs.berkel...	2018	876
8,114	GIANT: Globally Improved Approximate Newton Method for Distributed Optimization Shusen Wang Stevens Institute of Technology shusen.wang@stevens.edu Farbod Roosta-Khorasani University of Queensland fred.roosta@uq.edu.au Peng Xu Stanford University pengxu@stanford.edu Michael W. Mahoney University...	2018	877
8,115	Stochastic Cubic Regularization for Fast Nonconvex Optimization Nilesh Tripuraneni⇤ Mitchell Stern⇤ Chi Jin Jeffrey Regier Michael I. Jordan {nilesh_tripuraneni,mitchell,chijin,regier}@berkeley.edu jordan@cs.berkeley.edu University of California, Berkeley Abstract This paper proposes a stochastic ...	2018	878
8,116	Derivative Estimation in Random Design Yu Liu1, Kris De Brabanter1,2∗ 1Department of Computer Science, 2Department of Statistics Abstract We propose a nonparametric derivative estimation method for random design without having to estimate the regression function. The method is based on a variance-reducing l...	2018	879
8,117	Learning a High Fidelity Pose Invariant Model for High-resolution Face Frontalization Jie Cao, Yibo Hu, Hongwen Zhang, Ran He∗, Zhenan Sun National Laboratory of Pattern Recognition, CASIA Center for Research on Intelligent Perception and Computing, CASIA Center for Excellence in Brain Science and Intelligenc...	2018	88
8,118	Approximating Real-Time Recurrent Learning with Random Kronecker Factors Asier Mujika ∗ Department of Computer Science ETH Zürich, Switzerland asierm@inf.ethz.ch Florian Meier Department of Computer Science ETH Zürich, Switzerland meierflo@inf.ethz.ch Angelika Steger Department of Computer Science...	2018	880
8,119	Hyperbolic Neural Networks Octavian-Eugen Ganea∗ Dept. of Computer Science ETH Zürich Zurich, Switzerland Gary Bécigneul∗ Dept. of Computer Science ETH Zürich Zurich, Switzerland Thomas Hofmann Dept. of Computer Science ETH Zürich Zurich, Switzerland Abstract Hyperbolic spaces have recently ...	2018	881
8,120	Mean Field for the Stochastic Blockmodel: Optimization Landscape and Convergence Issues Soumendu Sunder Mukherjee∗ Interdisciplinary Statistical Research Unit (ISRU) Indian Statistical Institute, Kolkata Kolkata 700108, India soumendu041@gmail.com Purnamrita Sarkar∗ Department of Statistics and Data Sci...	2018	882
8,121	Fast Greedy MAP Inference for Determinantal Point Process to Improve Recommendation Diversity Laming Chen Hulu LLC Beijing, China laming.chen@hulu.com Guoxin Zhang∗ Kwai Inc. Beijing, China zhangguoxin@kuaishou.com Hanning Zhou Hulu LLC Beijing, China ericzhouh@gmail.com Abstract The deter...	2018	883
8,122	Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks Jie Hu∗ Momenta hujie@momenta.ai Li Shen∗ Visual Geometry Group University of Oxford lishen@robots.ox.ac.uk Samuel Albanie∗ Visual Geometry Group University of Oxford albanie@robots.ox.ac.uk Gang Sun Momenta sungang...	2018	884
8,123	Active Learning for Non-Parametric Regression Using Purely Random Trees Jack Goetz Ambuj Tewari University of Michigan Ann Arbor, MI 48109 {jrgoetz, tewaria, paulzim}@umich.edu Paul Zimmerman Abstract Active learning is the task of using labelled data to select additional points to label, with the g...	2018	885
8,124	DeepProbLog: Neural Probabilistic Logic Programming Robin Manhaeve KU Leuven robin.manhaeve@cs.kuleuven.be Sebastijan Dumanˇci´c KU Leuven sebastijan.dumancic@cs.kuleuven.be Angelika Kimmig Cardiff University KimmigA@cardiff.ac.uk Thomas Demeester∗ Ghent University - imec thomas.demeester@ugen...	2018	886
8,125	Image-to-image translation for cross-domain disentanglement Abel Gonzalez-Garcia Computer Vision Center agonzalez@cvc.uab.es Joost van de Weijer Computer Vision Center Universitat Autònoma de Barcelona Yoshua Bengio MILA Université de Montréal Abstract Deep image translation methods have recentl...	2018	887
8,126	Expanding Holographic Embeddings for Knowledge Completion Yexiang Xue⋆ Yang Yuan† Zhitian Xu⋆ Ashish Sabharwal‡ ⋆Dept. of Computer Science, Purdue University, West Lafayette, IN, USA † Dept. of Computer Science, Cornell University, Ithaca, NY, USA ‡ Allen Institute for Artiﬁcial Intelligence (AI2), Seat...	2018	888
8,127	Breaking the Curse of Horizon: Inﬁnite-Horizon Off-Policy Estimation Qiang Liu The University of Texas at Austin Austin, TX, 78712 lqiang@cs.utexas.edu Lihong Li Google Brain Kirkland, WA, 98033 lihong@google.com Ziyang Tang The University of Texas at Austin Austin, TX, 78712 ztang@cs.utexas.e...	2018	889
8,128	Provably Correct Automatic Subdifferentiation for Qualiﬁed Programs Sham M. Kakade University of Washington sham@cs.washington.edu Jason D. Lee University of Southern California jasonlee@marshall.usc.edu Abstract The Cheap Gradient Principle [Griewank and Walther, 2008] — the computational cost of com...	2018	89
8,129	TopRank: A Practical Algorithm for Online Stochastic Ranking Tor Lattimore DeepMind Branislav Kveton Google Shuai Li The Chinese University of Hong Kong Csaba Szepesvári DeepMind and University of Alberta Abstract Online learning to rank is a sequential decision-making problem where in each roun...	2018	890
8,130	ρ-POMDPs have Lipschitz-Continuous ϵ-Optimal Value Functions Mathieu Fehr1, Olivier Buffet2, Vincent Thomas2, Jilles Dibangoye3 1 École Normale Supérieure de la rue d’Ulm, Paris, France 2 Université de Lorraine, CNRS, Inria, LORIA, Nancy, France 3 Université de Lyon, INSA Lyon, Inria, CITI, Lyon, France mat...	2018	891
8,131	Minimax Estimation of Neural Net Distance Kaiyi Ji Department of ECE The Ohio State University Columbus, OH 43210 ji.367@osu.edu Yingbin Liang Department of ECE The Ohio State University Columbus, OH 43210 liang.889@osu.edu Abstract An important class of distance metrics proposed for training ge...	2018	892
8,132	Using Large Ensembles of Control Variates for Variational Inference Tomas Geffner College of Information and Computer Science University of Massachusetts Amherst, MA 01003 tgeffner@cs.umass.edu Justin Domke College of Information and Computer Science University of Massachusetts Amherst, MA 01003 d...	2018	893
8,133	Deep Generative Markov State Models Hao Wu1,2,∗, Andreas Mardt1,∗, Luca Pasquali1,∗, and Frank Noe1,† 1Dept. of Mathematics and Computer Science, Freie Universität Berlin, 14195 Berlin, Germany 2School of Mathematical Sciences, Tongji University, Shanghai, 200092, P.R. China Abstract We propose a deep generat...	2018	894
8,134	Zero-Shot Transfer with Deictic Object-Oriented Representation in Reinforcement Learning Oﬁr Marom1, Benjamin Rosman 1,2 1University of the Witwatersrand, Johannesburg, South Africa 2Council for Scientiﬁc and Industrial Research, Pretoria, South Africa Abstract Object-oriented representations in reinforceme...	2018	895
8,135	Practical Methods for Graph Two-Sample Testing Debarghya Ghoshdastidar Department of Computer Science University of Tübingen ghoshdas@informatik.uni-tuebingen.de Ulrike von Luxburg Department of Computer Science University of Tübingen Max Planck Institute for Intelligent Systems luxburg@informatik.uni...	2018	896
8,136	Point process latent variable models of larval zebraﬁsh behavior Anuj Sharma Columbia University Robert E. Johnson Harvard University Florian Engert Harvard University Scott W. Linderman∗ Columbia University Abstract A fundamental goal of systems neuroscience is to understand how neural activity ...	2018	897
8,137	Learning to Navigate in Cities Without a Map Piotr Mirowski, Matthew Koichi Grimes, Mateusz Malinowski, Karl Moritz Hermann, Keith Anderson, Denis Teplyashin, Karen Simonyan, Koray Kavukcuoglu, Andrew Zisserman, Raia Hadsell DeepMind London, United Kingdom {piotrmirowski, mkg, mateuszm, kmh, keithanderson, ...	2018	898
8,138	Fast greedy algorithms for dictionary selection with generalized sparsity constraints Kaito Fujii Graduate School of Information Sciences and Technology The University of Tokyo kaito_fujii@mist.i.u-tokyo.ac.jp Tasuku Soma Graduate School of Information Sciences and Technology The University of Tokyo t...	2018	899
8,139	Adaptive Sampling Towards Fast Graph Representation Learning Wenbing Huang1, Tong Zhang2, Yu Rong1, Junzhou Huang1 1 Tencent AI Lab. ; 2 Australian National University; hwenbing@126.com, tong.zhang@anu.edu.au, yu.rong@hotmail.com, joehhuang@tencent.com Abstract Graph Convolutional Networks (GCNs) have b...	2018	9
8,140	CatBoost: unbiased boosting with categorical features Liudmila Prokhorenkova1,2, Gleb Gusev1,2, Aleksandr Vorobev1, Anna Veronika Dorogush1, Andrey Gulin1 1Yandex, Moscow, Russia 2Moscow Institute of Physics and Technology, Dolgoprudny, Russia {ostroumova-la, gleb57, alvor88, annaveronika, gulin}@yandex-team....	2018	90
8,141	Acceleration through Optimistic No-Regret Dynamics Jun-Kun Wang College of Computing Georgia Institute of Technology Atlanta, GA 30313 jimwang@gatech.edu Jacob Abernethy College of Computing Georgia Institute of Technology Atlanta, GA 30313 prof@gatech.edu Abstract We consider the problem of min...	2018	900
8,142	Hybrid Retrieval-Generation Reinforced Agent for Medical Image Report Generation Christy Y. Li∗ Duke University yl558@duke.edu Xiaodan Liang† Carnegie Mellon University xiaodan1@cs.cmu.edu Zhiting Hu Carnegie Mellon University zhitingh@cs.cmu.edu Eric P. Xing Petuum, Inc epxing@cs.cmu.edu Ab...	2018	901
8,143	Dimensionally Tight Bounds for Second-Order Hamiltonian Monte Carlo Oren Mangoubi EPFL omangoubi@gmail.com Nisheeth K. Vishnoi EPFL nisheeth.vishnoi@gmail.com Abstract Hamiltonian Monte Carlo (HMC) is a widely deployed method to sample from highdimensional distributions in Statistics and Machine learn...	2018	902
8,144	Invertibility of Convolutional Generative Networks from Partial Measurements Fangchang Ma* MIT fcma@mit.edu Ulas Ayaz˚ MIT uayaz@mit.edu uayaz@lyft.com Sertac Karaman MIT sertac@mit.edu Abstract The problem of inverting generative neural networks (i.e., to recover the input latent code given...	2018	903
8,145	Towards Robust Detection of Adversarial Examples Tianyu Pang, Chao Du, Yinpeng Dong, Jun Zhu∗ Dept. of Comp. Sci. & Tech., State Key Lab for Intell. Tech. & Systems BNRist Center, THBI Lab, Tsinghua University, Beijing, China {pty17, du-c14, dyp17}@mails.tsinghua.edu.cn, dcszj@mail.tsinghua.edu.cn Abstract ...	2018	904
8,146	Bayesian Model-Agnostic Meta-Learning Jaesik Yoon∗3, Taesup Kim∗‡2, Ousmane Dia1, Sungwoong Kim4, Yoshua Bengio2,5, Sungjin Ahn‡6 1Element AI, 2MILA Université de Montréal, 3SAP, 4Kakao Brain, 5CIFAR Senior Fellow, 6Rutgers University Abstract Due to the inherent model uncertainty, learning to infer Bayesia...	2018	905
8,147	Learning Signed Determinantal Point Processes through the Principal Minor Assignment Problem Victor-Emmanuel Brunel Department of Mathematics Massachusetts Institute of Technology Cambridge, MA 02139 vebrunel@mit.edu Abstract Symmetric determinantal point processes (DPP) are a class of probabilistic mod...	2018	906
8,148	Direct Estimation of Differences in Causal Graphs Yuhao Wang Lab for Information & Decision Systems and Institute for Data, Systems and Society Massachusetts Institute of Technology Cambridge, MA 02139 yuhaow@mit.edu Chandler Squires Lab for Information & Decision Systems and Institute for Data, Syste...	2018	907
8,149	A2-Nets: Double Attention Networks Yunpeng Chen∗ National University of Singapore chenyunpeng@u.nus.edu Yannis Kalantidis Facebook Research yannisk@fb.com Jianshu Li National University of Singapore jianshu@u.nus.edu Shuicheng Yan Qihoo 360 AI Institute National University of Singapore eleyans...	2018	908
8,150	Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding Nan Rosemary Ke1,2, Anirudh Goyal1, Olexa Bilaniuk1, Jonathan Binas1, Michael C. Mozer3, Chris Pal1,2,4, Yoshua Bengio1† 1 Mila, Université de Montréal 2 Mila, Polytechnique Montréal 3 University of Colorado, Boulder 4 Element AI ...	2018	909
8,151	Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders Tengfei Ma∗ Jie Chen∗ Cao Xiao IBM Research Tengfei.Ma1@ibm.com, {chenjie,cxiao}@us.ibm.com Abstract Deep generative models have achieved remarkable success in various data domains, including images, time s...	2018	91
8,152	Ridge Regression and Provable Deterministic Ridge Leverage Score Sampling Shannon R. McCurdy California Institute for Quantitative Biosciences UC Berkeley Berkeley, CA 94702 smccurdy@berkeley.edu Abstract Ridge leverage scores provide a balance between low-rank approximation and regularization, and are ...	2018	910
8,153	Dynamic Network Model from Partial Observations Elahe Ghalebi TU Wien eghalebi@cps.tuwien.ac.at Baharan Mirzasoleiman Stanford University baharanm@cs.stanford.edu Radu Grosu TU Wien radu.grosu@tuwien.ac.at Jure Leskovec Stanford University jure@cs.stanford.edu Abstract Can evolving networks ...	2018	911
8,154	Overﬁtting or perfect ﬁtting? Risk bounds for classiﬁcation and regression rules that interpolate Mikhail Belkin The Ohio State University Daniel Hsu Columbia University Partha P. Mitra Cold Spring Harbor Laboratory Abstract Many modern machine learning models are trained to achieve zero or near-zero ...	2018	912
8,155	Actor-Critic Policy Optimization in Partially Observable Multiagent Environments Sriram Srinivasan∗,1 srsrinivasan@ Marc Lanctot∗,1 lanctot@ Vinicius Zambaldi1 vzambaldi@ Julien Pérolat1 perolat@ Karl Tuyls1 karltuyls@ Rémi Munos1 munos@ Michael Bowling1 bowlingm@ ...@google.com. 1DeepMi...	2018	913
8,156	End-to-end Symmetry Preserving Inter-atomic Potential Energy Model for Finite and Extended Systems Linfeng Zhang1, Jiequn Han1, Han Wang2,3,∗, Wissam A. Saidi4,†, Roberto Car1,5,6, Weinan E1,7,8,‡ 1 Program in Applied and Computational Mathematics, Princeton University, USA 2 Institute of Applied Physics an...	2018	914
8,157	Relational recurrent neural networks Adam Santoroα, Ryan Faulknerα, David Raposoα, Jack Raeαβ, Mike Chrzanowskiα, Théophane Weberα, Daan Wierstraα, Oriol Vinyalsα, Razvan Pascanuα, Timothy Lillicrapαβ Equal Contribution αDeepMind London, United Kingdom βCoMPLEX, Computer Science, University College Lond...	2018	915
8,158	Improved Expressivity Through Dendritic Neural Networks Xundong Wu Xiangwen Liu Wei Li Qing Wu School of Computer Science and Technology Hangzhou Dianzi University, Hangzhou, China wuxundong@gmail.com, wuq@hdu.edu.cn A typical biological neuron, such as a pyramidal neuron of the neocortex, receives th...	2018	916
8,159	DAGs with NO TEARS: Continuous Optimization for Structure Learning Xun Zheng1, Bryon Aragam1, Pradeep Ravikumar1, Eric P. Xing1,2 1Carnegie Mellon University 2Petuum Inc. {xunzheng,naragam,pradeepr,epxing}@cs.cmu.edu Abstract Estimating the structure of directed acyclic graphs (DAGs, also known as Bayesia...	2018	917
8,160	Kalman Normalization: Normalizing Internal Representations Across Network Layers Guangrun Wang Sun Yat-sen University wanggrun@mail2.sysu.edu.cn Jiefeng Peng Sun Yat-sen University jiefengpeng@gmail.com Ping Luo The Chinese University of Hong Kong pluo.lhi@gmail.com Xinjiang Wang SenseTime Group...	2018	918
8,161	Connectionist Temporal Classiﬁcation with Maximum Entropy Regularization Hu Liu Sheng Jin Changshui Zhang Institute for Artiﬁcial Intelligence, Tsinghua University (THUAI) Beijing National Research Center for Information Science and Technology (BNRist) State Key Lab of Intelligent Technologies and Systems...	2018	919
8,162	Deep, complex, invertible networks for inversion of transmission effects in multimode optical ﬁbres Oisín Moran,1 Piergiorgio Caramazza,2 Daniele Faccio,2 Roderick Murray-Smith1,* 1School of Computing Science, University of Glasgow, Scotland. oisin@inscribe.ai, Roderick.Murray-Smith@glasgow.ac.uk, 2School of ...	2018	92
8,163	Are GANs Created Equal? A Large-Scale Study Mario Lucic⋆ Karol Kurach⋆ Marcin Michalski Google Brain Olivier Bousquet Sylvain Gelly Abstract Generative adversarial networks (GAN) are a powerful subclass of generative models. Despite a very rich research activity leading to numerous interesting GAN a...	2018	920
8,164	Recurrent Transformer Networks for Semantic Correspondence Seungryong Kim1, Stephen Lin2, Sangryul Jeon1, Dongbo Min3, and Kwanghoon Sohn1,∗ 1Yonsei University, Seoul, South Korea, 2Microsoft Research, Beijing, China, 3Ewha Womans University, Seoul, South Korea {srkim89,cheonjsr,khsohn}@yonsei.ac.kr, stevelin...	2018	921
8,165	Generative Neural Machine Translation Harshil Shah1 David Barber1,2,3 1University College London 2Alan Turing Institute 3reinfer.io Abstract We introduce Generative Neural Machine Translation (GNMT), a latent variable architecture which is designed to model the semantics of the source and target sente...	2018	922
8,166	FRAGE: Frequency-Agnostic Word Representation Chengyue Gong1 cygong@pku.edu.cn Di He2 di_he@pku.edu.cn Xu Tan3 xu.tan@microsoft.com Tao Qin3 taoqin@microsoft.com Liwei Wang2,4 wanglw@cis.pku.edu.cn Tie-Yan Liu3 tie-yan.liu@microsoft.com 1Peking University 2Key Laboratory of Machine Perceptio...	2018	923
8,167	Variational Memory Encoder-Decoder Hung Le, Truyen Tran, Thin Nguyen and Svetha Venkatesh Applied AI Institute, Deakin University, Geelong, Australia {lethai,truyen.tran,thin.nguyen,svetha.venkatesh}@deakin.edu.au Abstract Introducing variability while maintaining coherence is a core task in learning to gen...	2018	924
8,168	Joint Active Feature Acquisition and Classiﬁcation with Variable-Size Set Encoding Hajin Shim1, Sung Ju Hwang1,2, Eunho Yang1,2 KAIST1, AItrics2, South Korea {shimazing, sjhwang82, eunhoy} @kaist.ac.kr Abstract We consider the problem of active feature acquisition where the goal is to sequentially select th...	2018	925
8,169	Data-Efﬁcient Hierarchical Reinforcement Learning Oﬁr Nachum Google Brain ofirnachum@google.com Shixiang Gu∗ Google Brain shanegu@google.com Honglak Lee Google Brain honglak@google.com Sergey Levine† Google Brain slevine@google.com Abstract Hierarchical reinforcement learning (HRL) is a prom...	2018	926
8,170	Veriﬁable Reinforcement Learning via Policy Extraction Osbert Bastani MIT obastani@csail.mit.edu Yewen Pu MIT yewenpu@mit.edu Armando Solar-Lezama MIT asolar@csail.mit.edu Abstract While deep reinforcement learning has successfully solved many challenging control tasks, its real-world applicabil...	2018	927
8,171	Stochastic Spectral and Conjugate Descent Methods Dmitry Kovalev1,2 Eduard Gorbunov1 Elnur Gasanov1,2 Peter Richtárik2,3,1 1Moscow Institute of Physics and Technology, Dolgoprudny, Russia 2King Abdullah University of Science and Technology, Thuwal, Saudi Arabia 3University of Edinburgh, Edinburgh, United ...	2018	928
8,172	A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization Zhize Li IIIS, Tsinghua University zz-li14@mails.tsinghua.edu.cn Jian Li IIIS, Tsinghua University lijian83@mail.tsinghua.edu.cn Abstract We analyze stochastic gradient algorithms for optimizing nonconvex, nonsmooth ﬁn...	2018	929
8,173	Scalable Hyperparameter Transfer Learning Valerio Perrone, Rodolphe Jenatton, Matthias Seeger, Cédric Archambeau Amazon Berlin, Germany {vperrone, jenatton, matthis, cedrica}@amazon.com Abstract Bayesian optimization (BO) is a model-based approach for gradient-free black-box function optimization, such as...	2018	93
8,174	Hierarchical Graph Representation Learning with Differentiable Pooling Rex Ying rexying@stanford.edu Stanford University Jiaxuan You jiaxuan@stanford.edu Stanford University Christopher Morris christopher.morris@udo.edu TU Dortmund University Xiang Ren xiangren@usc.edu University of Southern C...	2018	930
8,175	Robust Detection of Adversarial Attacks by Modeling the Intrinsic Properties of Deep Neural Networks Zhihao Zheng Department of Computer Science Brandeis University Waltham, MA 02453 zhihaozh@brandeis.edu Pengyu Hong Department of Computer Science Brandeis University Waltham, MA 02453 hongpeng@bra...	2018	931
8,176	Removing the Feature Correlation Effect of Multiplicative Noise Zijun Zhang University of Calgary zijun.zhang@ucalgary.ca Yining Zhang University of Calgary yining.zhang1@ucalgary.ca Zongpeng Li Wuhan University zongpeng@whu.edu.cn Abstract Multiplicative noise, including dropout, is widely used...	2018	932
8,177	The Effect of Network Width on the Performance of Large-batch Training Lingjiao Chen1 , Hongyi Wang1 , Jinman Zhao1, Paraschos Koutris, 1 Dimitris Papailiopoulos2 1Department of Computer Sciences, 2Department of Electrical and Computer Engineering University of Wisconsin-Madison Abstract Distributed i...	2018	933
8,178	Efﬁcient Loss-Based Decoding on Graphs for Extreme Classiﬁcation Itay Evron Computer Science Dept. The Technion, Israel evron.itay@gmail.com Edward Moroshko Electrical Engineering Dept. The Technion, Israel edward.moroshko@gmail.com Koby Crammer Electrical Engineering Dept. The Technion, Israel ...	2018	934
8,179	Scalable Methods for 8-bit Training of Neural Networks Ron Banner1∗, Itay Hubara2∗, Elad Hoffer2∗, Daniel Soudry2 {itayhubara, elad.hoffer, daniel.soudry}@gmail.com {ron.banner}@intel.com (1) Intel - Artiﬁcial Intelligence Products Group (AIPG) (2) Technion - Israel Institute of Technology, Haifa, Israel ...	2018	935
8,180	Solving Large Sequential Games with the Excessive Gap Technique Christian Kroer, Gabriele Farina, and Tuomas Sandholm Department of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 {ckroer,gfarina,sandholm}@cs.cmu.edu Abstract There has been tremendous recent progress on equilibrium-ﬁndi...	2018	936
8,181	Step Size Matters in Deep Learning Kamil Nar S. Shankar Sastry Electrical Engineering and Computer Sciences University of California, Berkeley Abstract Training a neural network with the gradient descent algorithm gives rise to a discrete-time nonlinear dynamical system. Consequently, behaviors that are t...	2018	937
8,182	A Reduction for Efﬁcient LDA Topic Reconstruction Matteo Almanza∗ Sapienza University Rome, Italy almanza@di.uniroma1.it Flavio Chierichetti† Sapienza University Rome, Italy flavio@di.uniroma1.it Alessandro Panconesi‡ Sapienza University Rome, Italy ale@di.uniroma1.it Andrea Vattani Spiketra...	2018	938
8,183	Convex Elicitation of Continuous Real Properties Jessica Finocchiaro Department of Computer Science University of Colorado, Boulder jessica.finocchiaro@colorado.edu Rafael Frongillo Department of Computer Science University of Colorado, Boulder raf@colorado.edu Abstract A property or statistic of a ...	2018	939
8,184	Wasserstein Distributionally Robust Kalman Filtering Soroosh Shaﬁeezadeh-Abadeh Viet Anh Nguyen Daniel Kuhn École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland {soroosh.shafiee,viet-anh.nguyen,daniel.kuhn} @epfl.ch Peyman Mohajerin Esfahani Delft Center for Systems and Control, TU Delf...	2018	94
8,185	The Nearest Neighbor Information Estimator is Adaptively Near Minimax Rate-Optimal Jiantao Jiao Department of Electrical Engineering and Computer Sciences University of California, Berkeley jiantao@berkeley.edu Weihao Gao Department of ECE Coordinated Science Laboratory University of Illinois at Urban...	2018	940
8,186	Bandit Learning with Positive Externalities Virag Shah Management Science and Engineering Stanford University California, USA 94305 virag@stanford.edu Jose Blanchet Management Science and Engineering Stanford University California, USA 94305 jblanche@stanford.edu Ramesh Johari Management Science...	2018	941
8,187	Minimax statistical learning with Wasserstein distances Jaeho Lee Maxim Raginsky {jlee620, maxim}@illinois.edu⇤ Abstract As opposed to standard empirical risk minimization (ERM), distributionally robust optimization aims to minimize the worst-case risk over a larger ambiguity set containing the original...	2018	942
8,188	Dirichlet belief networks for topic structure learning He Zhao1, Lan Du1∗, Wray Buntine1, and Mingyuan Zhou2∗ 1Faculty of Information Technology, Monash University, Australia 2McCombs School of Business, The University of Texas at Austin, USA Abstract Recently, considerable research effort has been devoted to...	2018	943
8,189	Efﬁcient Stochastic Gradient Hard Thresholding Pan Zhou∗ Xiao-Tong Yuan† Jiashi Feng∗ ∗Learning & Vision Lab, National University of Singapore, Singapore † B-DAT Lab, Nanjing University of Information Science & Technology, Nanjing, China pzhou@u.nus.edu xtyuan@nuist.edu.cn elefjia@nus.edu.sg Abstract ...	2018	944
8,190	Learning long-range spatial dependencies with horizontal gated recurrent units Drew Linsley, Junkyung Kim, Vijay Veerabadran, Charlie Windolf, Thomas Serre Carney Institute for Brain Science Department of Cognitive Linguistic & Psychological Sciences Brown University Providence, RI 02912 {drew_linsley,jun...	2018	945
8,191	Tight Bounds for Collaborative PAC Learning via Multiplicative Weights∗ Jiecao Chen Computer Science Department Indiana University at Bloomington jiecchen@iu.edu Qin Zhang Computer Science Department Indiana University at Bloomington qzhangcs@indiana.edu Yuan Zhou Computer Science Department Ind...	2018	946
8,192	(Probably) Concave Graph Matching Haggai Maron Weizmann Institute of Science Rehovot, Israel haggai.maron@weizmann.ac.il Yaron Lipman Weizmann Institute of Science Rehovot, Israel yaron.lipman@weizmann.ac.il Abstract In this paper, we address the graph matching problem. Following the recent works ...	2018	947
8,193	HOUDINI: Lifelong Learning as Program Synthesis Lazar Valkov University of Edinburgh L.Valkov@sms.ed.ac.uk Dipak Chaudhari Rice University dipakc@rice.edu Akash Srivastava University of Edinburgh Akash.Srivastava@ed.ac.uk Charles Sutton University of Edinburgh, The Alan Turing Institute, and Goo...	2018	948
8,194	Video Prediction via Selective Sampling Jingwei Xu, Bingbing Ni∗, Xiaokang Yang MoE Key Lab of Artiﬁcial Intelligence, AI Institute SJTU-UCLA Joint Research Center on Machine Perception and Inference, Shanghai Jiao Tong University, Shanghai 200240, China Shanghai Institute for Advanced Communication and D...	2018	949
8,195	SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator Cong Fang1 ∗ Chris Junchi Li2 Zhouchen Lin1† Tong Zhang2 1Key Lab. of Machine Intelligence (MoE), School of EECS, Peking University 2Tencent AI Lab {fangcong, zlin}@pku.edu.cn junchi.li.duke@gmail.com ...	2018	95
8,196	Manifold-tiling Localized Receptive Fields are Optimal in Similarity-preserving Neural Networks Anirvan M. Sengupta†‡ Mariano Tepper‡⇤ Cengiz Pehlevan‡⇤ Alexander Genkin§ Dmitri B. Chklovskii‡§ †Rutgers University ‡Flatiron Institute §NYU Langone Medical Center anirvans@physics.rutgers.edu, alexande...	2018	950
8,197	Snap ML: A Hierarchical Framework for Machine Learning Celestine Dünner∗1 Thomas Parnell∗1∗ Dimitrios Sarigiannis1 Nikolas Ioannou1 Andreea Anghel1 Gummadi Ravi2 Madhusudanan Kandasamy2 Haralampos Pozidis1 1IBM Research, Zurich, Switzerland 2IBM Systems, Bangalore, India {cdu,tpa,rig,nio,aan}@zurich.ibm.c...	2018	951
8,198	Embedding Logical Queries on Knowledge Graphs William L. Hamilton Payal Bajaj Marinka Zitnik Dan Jurafsky† Jure Leskovec {wleif, pbajaj, jurafsky}@stanford.edu, {jure, marinka}@cs.stanford.edu Stanford University, Department of Computer Science, †Department of Linguistics Abstract Learning low-dimensi...	2018	952
8,199	Parsimonious Bayesian deep networks Mingyuan Zhou Department of IROM, McCombs School of Business The University of Texas at Austin, Austin, TX 78712 mingyuan.zhou@mccombs.utexas.edu Abstract Combining Bayesian nonparametrics and a forward model selection strategy, we construct parsimonious Bayesian deep n...	2018	953

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