转摘【最全】机器学习顶会 ICML 2018 接收论文列表
新智元推荐
来源：专知（ID：Quan_Zhuanzhi）
**【新智元导读】**机器学习领域最具影响力的学术会议之一的ICML将于2018年7月10日-15日在瑞典斯德哥尔摩举行。ICML是机器学习领域顶级会议，由国际机器学习协会（International Machine Learning Society）主办。今年人工智能顶会JCAI2018也将于 7月 13 日 - 7 月 19 日 在瑞典斯德哥尔摩举行，很多人可能同时会参加这两个会议，期待七月份的盛会。
详细录用名单日前已经公布，可参见：https://icml.cc/Conferences/2018/AcceptedPapersInitial
论文列表：
ICML 2018 Accepted Papers
Tempered Adversarial NetworksMehdi S. M. Sajjadi (Max Planck Institute for Intelligent Systems) · Bernhard Schölkopf (MPI for Intelligent Systems Tübingen, Germany)
Adaptive Three Operator Splitting
Fabian Pedregosa (UC Berkeley) · Gauthier Gidel (MILA)
INSPECTRE: Privately Estimating the UnseenJayadev Acharya (Cornell University) · Gautam Kamath (MIT) · Ziteng Sun (Cornell University) · Huanyu Zhang (Cornell University)
Topological mixture estimationSteve Huntsman (BAE Systems FAST Labs)
On Nesting Monte Carlo EstimatorsTom Rainforth (University of Oxford) · Rob Cornish (Oxford) · Hongseok Yang (KAIST) · andrew warrington (University of Oxford) · Frank Wood (University of Oxford)
Anonymous Walk EmbeddingsSERGEY IVANOV (SKOLTECH & CRITEO) · Evgeny Burnaev (Skoltech)
**Do Outliers Ruin Collaboration?**Mingda Qiao (IIIS, Tsinghua University)
Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex OptimizationUmut Simsekli (Telecom ParisTech) · Cagatay Yildiz (Aalto University) · Than Nguyen (Telecom ParisTech) · Ali Cemgil (Bogazici University) · Gaël RICHARD (Télécom ParisTech)
Variational Network Inference: Strong and Stable with Concrete SupportAmir Dezfouli (UNSW) · Edwin Bonilla (UNSW) · Richard Nock (Data61, The Australian National University and the University of Sydney)
Semi-Supervised Learning on Data Streams via Temporal Label PropagationTal Wagner (MIT) · Sudipto Guha (Amazon) · Shiva Kasiviswanathan (Amazon) · Nina Mishra (Amazon)
Learning Diffusion using HyperparametersDimitrios Kalimeris (Harvard University) · Yaron Singer (Harvard) · Karthik Subbian (Facebook) · Udi Weinsberg (Facebook)
Distributional Optimization from SamplesYaron Singer (Harvard) · Eric Balkanski (Harvard) · Nir Rosenfeld (Harvard University) · Amir Globerson (Tel Aviv University, Google)
Approximation Guarantees for Adaptive SamplingEric Balkanski (Harvard) · Yaron Singer (Harvard)
Safe Element Screening for Submodular Function MinimizationWeizhong Zhang (Zhejiang University & Tencent AI Lab) · Bin Hong (Zhejiang University) · Lin Ma (Tencent AI Lab) · Wei Liu (Tencent AI Lab) · Tong Zhang (Tecent AI Lab)
Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical AnalysisPengtao Xie (Carnegie Mellon University) · Wei Wu (Carnegie Mellon University) · Eric Xing (Carnegie Mellon University)
An Algorithmic Framework of Variable Metric Over-Relaxed Hybrid Proximal Extra-Gradient MethodLi Shen (Tencent AI Lab) · Peng Sun (Tencent AI Lab) · Yitong Wang (Tencent AI Lab) · Wei Liu (Tencent AI Lab) · Tong Zhang (Tecent AI Lab)
Nonoverlap-Promoting Variable SelectionPengtao Xie (Carnegie Mellon University) · Hongbao Zhang (Petuum Inc) · Eric Xing (Carnegie Mellon University)
Spatio-temporal Bayesian On-line Changepoint Detection with Model SelectionJeremias Knoblauch (Warwick University) · Theodoros Damoulas (University of Warwick)
Improved Training of Generative Adversarial Networks Using Representative FeaturesDuhyeon Bang (Yonsei univ.) · Hyunjung Shim (Yonsei University)
End-to-end Active Object Tracking via Reinforcement LearningWenhan Luo (Tencent AI Lab) · Peng Sun (Tencent AI Lab) · Fangwei Zhong (Peking University) · Wei Liu (Tencent AI Lab) · Tong Zhang (Tecent AI Lab) · Yizhou Wang (Peking University)
Bayesian Quadrature for Multiple Related IntegralsXiaoyue Xi (Imperial College London) · Francois-Xavier Briol (University of Warwick) · Mark Girolami (Imperial College London)
Exploring Hidden Dimensions in Accelerating Convolutional Neural NetworksZhihao Jia (Stanford University) · Sina Lin (Microsoft) · Charles Qi (Stanford University) · Alex Aiken (Stanford University)
Theoretical Analysis of Image-to-Image Translation with Adversarial LearningPAN XUDONG (Fudan University) · Mi Zhang (Fudan University) · Daizong Ding (Fudan University)
Implicit Regularization in Nonconvex Statistical EstimationCong Ma (Princeton University) · Kaizheng Wang (Princeton University) · Yuejie Chi (CMU) · Yuxin Chen (Princeton University)
Goodness-of-fit Testing for Discrete Distributions via Stein DiscrepancyJiasen Yang (Purdue University) · Qiang Liu (UT Austin) · Vinayak A Rao (Purdue University) · Jennifer Neville (Purdue University)
An Iterative, Sketching-based Framework for Ridge RegressionAgniva Chowdhury (Purdue University) · Jiasen Yang (Purdue University) · Petros Drineas (Purdue University)
Improving Sign Random Projections With Additional InformationKeegan Kang (Singapore University Of Technology And Design) · Wei Pin Wong (Singapore University of Technology and Design)
MSplit LBI: Realizing Feature Selection and Dense Estimation Simultaneously in Few-shot and Zero-shot LearningBo Zhao (Peking University) · Xinwei Sun (Peking University) · Yanwei Fu (Fudan university) · Yuan Yao (The Chinese Hong Kong Science Tech) · Yizhou Wang (Peking University)
On the Spectrum of Random Features Maps of High Dimensional DataZhenyu Liao (L2S, CentraleSupelec) · Romain Couillet (CentralSupélec)
SMAC: Simultaneous Mapping and Clustering Using Spectral Decompositionschandrajit bajaj (University of Texas at Austin) · Tingran Gao (University of Chicago) · Zihang He (Tsinghua University) · Qixing Huang (The University of Texas at Austin) · Zhenxiao Liang (Tsinghua University)
**Which Training Methods for GANs do actually Converge?**Lars Mescheder (MPI Tübingen) · Andreas Geiger (MPI-IS and University of Tuebingen) · Sebastian Nowozin (Microsoft Research)
Neural Photometric Stereo Reconstruction for General Reflectance SurfacesTatsunori Taniai (RIKEN AIP) · Takanori Maehara (RIKEN AIP)
Adversarial Learning with Local Coordinate CodingJiezhang Cao (South China University of Technology) · Yong Guo (South China University of Technology) · Chunhua Shen (University of Adelaide) · Qingyao Wu (South China University of Technology) · Mingkui Tan (South China University of Technology)
Junction Tree Variational Autoencoder for Molecular Graph GenerationWengong Jin (MIT Computer Science and Artificial Intelligence Laboratory) · Regina Barzilay (MIT CSAIL) · Tommi Jaakkola (MIT)
DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse CodingCMLA Thomas Moreau (CMLA, ENS Paris-Saclay) · Laurent Oudre (Universite Paris 13) · CMLA Nicolas Vayatis (CMLA, ENS Paris Saclay)
Gradually Updated Neural Networks for Large-Scale Image RecognitionSiyuan Qiao (Johns Hopkins University) · Zhishuai Zhang (Johns Hopkins University) · Wei Shen (Shanghai University) · Bo Wang (Hikvision Research Institue) · Alan Yuille (Johns Hopkins University)
Blind Justice: Fairness with Encrypted Sensitive Attributes
Niki Kilbertus (MPI Tübingen & Cambridge) · Adria Gascon (The Alan Turing Institute / Warwick University) · Matt Kusner (Alan Turing Institute) · Michael Veale (UCL) · Krishna Gummadi (MPI-SWS) · Adrian Weller (University of Cambridge, Alan Turing Institute)
Structured Evolution with Compact Architectures for Scalable Policy OptimizationKrzysztof Choromanski (Google Brain Robotics) · Mark Rowland (University of Cambridge) · Vikas Sindhwani (Google) · Richard E Turner (University of Cambridge) · Adrian Weller (University of Cambridge, Alan Turing Institute)
Discovering Interpretable Representations for Both Deep Generative and Discriminative ModelsTameem Adel (University of Cambridge) · Zoubin Ghahramani (University of Cambridge & Uber) · Adrian Weller (University of Cambridge, Alan Turing Institute)
Neural Program Synthesis from Diverse Demonstration VideosShao-Hua Sun (University of Southern California) · Hyeonwoo Noh (POSTECH) · Sriram Somasundaram (University of Southern California) · Joseph Lim (Univ. of Southern California)
Learning Low-Dimensional Temporal RepresentationsBing Su (Institute of Software Chinese Academy of Sciences)
Weakly consistent optimal pricing algorithms in repeated posted-price auctions with strategic buyerAlexey Drutsa (Yandex; MSU)
Fast Maximization of Non-Submodular, Monotonic Functions on the Integer LatticeAlan Kuhnle (University of Florida) · J. Smith (University of Florida) · Victoria Crawford (University of Florida) · My Thai (University of Florida)
Learning the Reward Function for a Misspecified ModelErik Talvitie (Franklin & Marshall College)
Information Theoretic Guarantees for Empirical Risk Minimization with Applications to Big Data and Model SelectionIbrahim Alabdulmohsin (Saudi Aramco)
Message Passing Stein Variational Gradient DescentJingwei Zhuo (Tsinghua University) · Chang Liu (Tsinghua University) · Jiaxin Shi (Tsinghua University) · Jun Zhu (Tsinghua University) · Ning Chen () · Bo Zhang (Tsinghua University)
Towards Binary-Valued Gates for Robust LSTM TrainingDi He (Microsoft Research) · Zhuohan Li (Peking University) · Fei Tian (Microsoft Research) · Wei Chen (Microsoft Research) · Tao Qin (Microsoft Research Asia) · Liwei Wang (Peking University) · Tieyan Liu ()
Learning Representations and Generative Models for 3D Point CloudsPanagiotis Achlioptas (Stanford) · Olga Diamanti (Stanford) · Ioannis Mitliagkas (MILA, UdeM) · Leonidas Guibas (Stanford University)
Parallel Bayesian Network Structure LearningTian Gao (IBM Research) · Dennis Wei (IBM Research)
Batched Bayesian Optimization via Multi-objective Acquisition Ensemble for Automated Analog Circuit DesignWenlong Lyu (Fudan University) · Fan Yang (Fudan University) · Changhao Yan () · Dian Zhou (Department of Electrical Engineering The University of Texas at Dallas Richardso) · Xuan Zeng (Fudan University)
Human Activity Prediction Using Sequence Earley AlgorithmSiyuan Qi (UCLA) · Baoxiong Jia (Peking University) · University of California Yingnian Wu (University of California, Los Angeles) · Song-Chun Zhu (UCLA)
Stochastic Proximal Algorithms for AUC MaximizationMichael Natole Jr (University at Albany) · Yiming Ying (SUNY Albany) · Siwei Lyu (University at Albany, State University of New York)
Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local MinimaSimon Du (Carnegie Mellon University) · Jason Lee (University of Southern California) · Yuandong Tian (Facebook AI Research) · Aarti Singh (Carnegie Mellon University) · Barnabás Póczos (CMU)
Theoretical Insights into the Optimization Landscape and Generalization Ability of Over-parametrized Neural NetworksSimon Du (Carnegie Mellon University) · Jason Lee (University of Southern California)
Coded Sparse Matrix MultiplicationSinong Wang (The Ohio State University) · Jiashang Liu (The Ohio State University) · Ness Shroff (The Ohio State University)
Invariance of Weight Distributions in Rectified MLPsSusumu Tsuchida (The University of Queensland) · Fred Roosta (University of Queensland) · Marcus Gallagher (University of Queensland)
Video Prediction with Appearance and Motion ConditionsYunseok Jang (Seoul National University) · Gunhee Kim (Seoul National University) · Yale Song (Microsoft AI & Research)
Scalable Deletion-Robust Submodular Maximization: Data Summarization with Privacy and Fairness ConstraintsEhsan Kazemi (Yale) · Morteza Zadimoghaddam (Google) · Amin Karbasi (Yale)
Theoretical Analysis of Sparse Subspace Clustering with Missing EntriesManolis Tsakiris (Johns Hopkins University) · Rene Vidal (Johns Hopkins University)
Binary Partitions with Approximate Minimum ImpurityEduardo Laber (PUC-RIO) · Marco Molinaro (PUC-RIO) · Felipe de A. Mello Pereira (Pontifícia Universidade Católica do Rio de Janeiro)
A Riemannian approach for structured low-rank matrix learningPratik Kumar Jawanpuria (Microsoft) · Bamdev Mishra (Microsoft)
The Generalization Error of Dictionary Learning with Moreau EnvelopesALEXANDROS GEORGOGIANNIS (TECHNICAL UNIVERSITY OF CRETE)
Understanding Generalization and Optimization Performance of Deep CNNsPan Zhou (National University of Singapore) · Jiashi Feng (National University of Singapore)
Learning Compact Neural Networks with RegularizationSamet Oymak (University of California, Riverside)
PDE-Net: Learning PDEs from DataZichao Long (Peking University) · Yiping Lu (Peking University) · Xianzhong Ma (Peking University) · Bin Dong (Peking University)
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential EquationsYiping Lu (Peking University) · Aoxiao Zhong (Zhejiang University) · Quanzheng Li (Mass General Hospital, Harvard Medical School) · Bin Dong (Peking University)
Augment and Reduce: Stochastic Inference for Large Categorical DistributionsFrancisco Ruiz (Columbia University) · Michalis Titsias (Athens University of Economics and Business) · Adji Bousso Dieng (Columbia University) · David Blei (Columbia University)
Out-of-sample extension of graph adjacency spectral embeddingKeith Levin (University of Michigan) · Fred Roosta (University of Queensland) · Michael Mahoney (UC Berkeley) · Carey Priebe (Johns Hopkins University)
Generalization without Systematicity: On the Compositional Skills of Sequence-to-Sequence Recurrent NetworksBrenden Lake (New York University) · Marco Baroni (Facebook Artificial Intelligence Research)
Learn to Exploration with Meta Policy GradientTianbing Xu (Baidu Research, USA) · Jian Peng (UIUC) · Liang Zhao (Baidu Research USA) · Wei Xu (Baidu Research) · Qiang Liu (UT Austin)
Fast Stochastic AUC Maximization with O(1/n)O(1/n)-Convergence RateMingrui Liu (The University of Iowa) · Xiaoxuan Zhang (University of Iowa) · Zaiyi Chen () · Tianbao Yang (The University of Iowa)
**An Alternative View: When Does SGD Escape Local Minima?**Bobby Kleinberg (Cornell) · Yuanzhi Li (Princeton University) · Yang Yuan (Cornell University)
Dependent Relational Gamma Process Models for Dynamic NetworksSikun Yang (TU Darmstadt) · Heinz Koeppl (TU Darmstadt)
Coordinated Exploration in Concurrent Reinforcement LearningMaria Dimakopoulou (Stanford) · Benjamin Van Roy (Stanford University)
Geodesic Convolutional Shape OptimizationPierre Baque (EPFL) · Edoardo Remelli (epfl) · Francois Fleuret (Idiap research institute) · EPFL Pascal Fua (EPFL, Switzerland)
Tight Regret Bounds for Bayesian Optimization in One DimensionJonathan Scarlett (National University of Singapore)
Active Testing: An Efficient and Robust Framework for Estimating AccuracyPhuc Nguyen (UC Irvine) · Charless Fowlkes (UC Irvine) · Deva Ramanan (Carnegie Mellon University)
Non-convex Conditional Gradient Slidingchao qu (technion) · Yan Li (Georgia Institute of Technology) · Huan Xu (Georgia Tech)
Spectrally approximating large graphs with smaller graphsAndreas Loukas (EPFL) · Pierre Vandergheynst (École polytechnique fédérale de Lausanne)
Quickshift++: Provably Good Initializations for Sample-Based Mean ShiftHeinrich Jiang (Google) · Jennifer Jang (Uber) · Samory Kpotufe (Princeton University)
Bayesian Coreset Construction via Greedy Iterative Geodesic AscentTrevor Campbell (MIT) · Tamara Broderick (MIT)
Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes FlowXiao Zhang (University of Virginia) · Simon Du (Carnegie Mellon University) · Quanquan Gu (University of Virginia--> UCLA)
Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted LabelsLu Jiang (Google) · Zhengyuan Zhou (Stanford University) · Thomas Leung (Google Inc) · Li-Jia Li (Google) · Li Fei-Fei (Stanford University & Google)
Adaptive Sampled Softmax with Kernel Based SamplingGuy Blanc (Stanford University) · Steffen Rendle (Google)
Black Box FDRWesley Tansey (Columbia University) · Yixin Wang (Columbia University) · David Blei (Columbia University) · Raul Rabadan (Columbia University Medical Center)
Graphical Nonconvex Optimization for Optimal Estimation in Gaussian Graphical ModelsQiang Sun (University of Toronto) · Kean Tan (University of Minnesota Twin Cities) · Han Liu (Princeton University) · Tong Zhang (Tecent AI Lab)
Policy Optimization with DemonstrationsBingyi Kang (National University of Singapore) · Jiashi Feng (National University of Singapore)
Learning to Explain: An Information-Theoretic Perspective on Model InterpretationJianbo Chen (University of California, Berkeley) · Le Song (Georgia Institute of Technology) · Martin Wainwright (University of California at Berkeley) · Michael Jordan (UC Berkeley)
Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process RegressionHaitao Liu (Rolls-Royce@NTU Corp Lab) · Jianfei Cai (Nanyang Technological University) · Yi Wang (Rolls-Royce Singapore) · Yew Soon ONG (Nanyang Technological University)
The Uncertainty Bellman Equation and ExplorationBrendan O'Donoghue (DeepMind) · Ian Osband (Google DeepMind) · Remi Munos (DeepMind) · Vlad Mnih (Google Deepmind)
Deep Asymmetric Multi-task Feature LearningHae Beom Lee (UNIST) · Eunho Yang (KAIST / AItrics) · Sung Ju Hwang (KAIST)
Learning Semantic Representations for Unsupervised Domain AdaptationShaoan Xie (Sun Yat-sen University) · Zibin Zheng ()
K-Beam Subgradient Descent for Minimax OptimizationJihun Hamm (The Ohio State University) · Yung-Kyun Noh (Seoul National University)
Asynchronous Byzantine Machine LearningGeorgios Damaskinos (EPFL) · El Mahdi El Mhamdi (EPFL) · Rachid Guerraoui (EPFL) · Rhicheek Patra (EPFL) · Mahsa Taziki (EPFL)
Differentially Private Database Release via Kernel Mean EmbeddingsMatej Balog (University of Cambridge and MPI Tübingen) · Ilya Tosltikhin (Max Planck Institute for Intelligent Systems, Tübingen) · Bernhard Schölkopf (MPI for Intelligent Systems Tübingen, Germany)
Learning with AbandonmentRamesh Johari (Stanford University) · Sven Schmit (Stanford University)
Rapid Adaptation with Conditionally Shifted NeuronsTsendsuren Munkhdalai (Microsoft Research) · Xingdi Yuan (Microsoft Maluuba) · Soroush Mehri (Microsoft Research) · Adam Trischler (Microsoft Research)
PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive LearningYunbo Wang (Tsinghua University) · Zhifeng Gao (Tsinghua University) · Mingsheng Long (Tsinghua University) · Jianmin Wang (Tsinghua University) · Philip Yu (UIC)
The Power of Interpolation: Understanding the Effectiveness of SGD in Modern Over-parametrized LearningSiyuan Ma (The Ohio State University) · Raef Bassily () · Mikhail Belkin (Ohio State University)
An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement LearningDhruv Malik (UC Berkeley) · Malayandi Palaniappan (UC Berkeley) · Jaime Fisac (UC Berkeley) · Dylan Hadfield-Menell (UC Berkeley) · Stuart Russell (UC Berkeley) · EECS Anca Dragan (EECS Department, University of California, Berkeley)
Dimensionality-Driven Learning with Noisy LabelsXingjun Ma (The University of Melbourne) · Yisen Wang (Tsinghua University) · Michael E. Houle (National Institute of Informatics) · Shuo Zhou (The University of Melbourne) · Sarah Erfani (University of Melbourne) · Shutao Xia (Tsinghua University) · Sudanthi Wijewickrema (University of Melbourne) · James Bailey (The University of Melbourne)
Rectify Heterogeneous Model with Semantic MappingHan-Jia Ye (Nanjing University) · De-Chuan Zhan (Nanjing University) · Yuan Jiang (Nanjing University) · Zhi-Hua Zhou (Nanjing University)
Synthesizing Programs for Images using Reinforced Adversarial LearningIaroslav Ganin (Montreal Institute for Learning Algorithms) · Tejas Kulkarni (DeepMind) · Igor Babuschkin () · S. M. Ali Eslami (DeepMind) · Oriol Vinyals (DeepMind)
Fast Information-theoretic Bayesian Optimisation
Binxin Ru (University of Oxford) · Michael A Osborne (U Oxford) · Mark Mcleod (University of Oxford) · Diego Granziol (Oxford)
Local Convergence Properties of SAGA/Prox-SVRG and AccelerationClarice
Poon (University of Cambridge) · Jingwei Liang (University of Cambridge) · Carola Schoenlieb (Cambridge University)
Let’s be honest: An optimal no-regret framework for zero-sum gamesYa-Ping Hsieh (École Polytechnique Fédérale d) · Ehsan Asadi Kangarshahi (University of Cambridge) · Mehmet Fatih Sahin (EPFL) · Volkan Cevher (EPFL)
Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes TheoryRon Amit (Technion – Israel Institute of Technology) · Ron Meir (Technion Israeli Institute of Technology)
An Estimation and Analysis Framework for the Rasch ModelAndrew Lan (Princeton University) · Mung Chiang (Purdue University) · Christoph Studer (Cornell University)
PIPPS: Flexible Model-Based Policy Search Robust to the Curse of ChaosPaavo Parmas (Okinawa Institute of Science and Technology Graduate University) · Kenji Doya (Okinawa Institute of Science and Technology) · Carl Rasmussen (-) · Jan Peters (TU Darmstadt + Max Planck Institute for Intelligent Systems)
Comparison-Based Random ForestsSiavash Haghiri (University of Tübingen) · Damien Garreau (Max Planck Institute) · Ulrike von Luxburg (University of Tübingen)
Gradient descent with identity initialization efficiently learns positive definite linear transformations by deep residual networksPeter Bartlett (UC Berkeley) · Dave Helmbold () · Phil Long (Google)
Semi-Amortized Variational AutoencodersYoon Kim (Harvard University) · Sam Wiseman (Harvard University) · Andrew Miller (Harvard) · David Sontag (Massachusetts Institute of Technology) · Alexander Rush (Harvard University)
Large-Scale Cox Process Inference using Variational Fourier FeaturesST John (PROWLER.io) · James Hensman (PROWLER.io)
Best Arm Identification in Linear Bandits with Linear Dimension DependencyChao Tao (Indiana University Bloomington) · Saúl A. Blanco (Indiana University) · Yuan Zhou (Indiana University Bloomington)
Data-Dependent Stability of Stochastic Gradient DescentIlja Kuzborskij (University of Milan) · Christoph Lampert (IST Austria)
Learning One Convolutional Layer with Overlapping PatchesSurbhi Goel (University of Texas at Austin) · Adam Klivans (University of Texas at Austin) · Raghu Meka (UCLA)
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic ActorTuomas Haarnoja (UC Berkeley) · Aurick Zhou (UC Berkeley) · Pieter Abbeel (OpenAI / UC Berkeley) · Sergey Levine (Berkeley)
Visualizing and Understanding Atari AgentsSamuel Greydanus (Oregon State University) · Anurag Koul (Oregon State University) · Jonathan Dodge (Oregon State University) · Alan Fern (Oregon State University)
Probabilistic Boolean Tensor DecompositionTammo Rukat (University of Oxford) · Christopher Holmes (University of Oxford) · Christopher Yau (University of Birmingham)
Dynamic Regret of Strongly Adaptive MethodsLijun Zhang (Nanjing University) · Tianbao Yang (The University of Iowa) · rong jin (alibaba group) · Zhi-Hua Zhou (Nanjing University)
Active Learning with Logged DataSongbai Yan (University of California San Diego) · Kamalika Chaudhuri (University of California at San Diego) · Tara Javidi (University of California San Diego)
Learning to Reweight Examples for Robust Deep LearningMengye Ren (Uber ATG / University of Toronto) · Wenyuan Zeng () · Bin Yang (University of Toronto) · Raquel Urtasun (University of Toronto)
An Optimal Control Approach to Deep Learning and Applications to Discrete-Weight Neural NetworksQianxiao Li (Institute of High Performance Computing, A*STAR, Singapore) · IHPC Shuji Hao (IHPC, A*STAR)
Deep linear networks with arbitrary loss: All local minima are globalThomas Laurent (Loyola Marymount University) · James von Brecht (CSULB)
Communication Efficient Gradient CodingMin Ye (Princeton University) · Emmanuel Abbe ()
Variable Selection via Penalized Neural Network: a Drop-Out-One Loss ApproachMao Ye (PURDUE UNIVERSITY) · Yan Sun (Purdue University)
Adaptive Exploration-Exploitation Tradeoff for Opportunistic BanditsHuasen Wu () · Xueying Guo (University of California Davis) · Xin Liu ()
Composite Marginal Likelihood Methods for Random Utility ModelsZhibing Zhao (Rensselaer Polytechnic Institute) · Lirong Xia (RPI)
Reviving and Improving Recurrent Back-PropagationRenjie Liao (University of Toronto) · Yuwen Xiong (Uber ATG / University of Toronto) · Ethan Fetaya (University of Toronto) · Lisa Zhang (University of Toronto) · KiJung Yoon (The University of Texas at Austin) · Zachary S Pitkow (Baylor College of Medicine / Rice University) · Raquel Urtasun (University of Toronto) · Richard Zemel (Vector Institute)
Accelerated Spectral RankingArpit Agarwal (University of Pennsylvania) · Prathamesh Patil (University of Pennsylvania) · Shivani Agarwal (University of Pennsylvania)
Dropout Training, Data-dependent Regularization, and Generalization BoundsWenlong Mou (UC Berkeley) · Yuchen Zhou (University of Wisconsin, Madison) · Jun Gao (Peking University) · Liwei Wang (Peking University)
Unbiased Objective Estimation in Predictive OptimizationShinji Ito (NEC Corporation) · Akihiro Yabe (NEC Corporation) · Ryohei Fujimaki (-)
Dissecting Adam: The Sign, Magnitude and Variance of Stochastic GradientsLukas Balles (Max Planck Institute for Intelligent Systems) · Philipp Hennig (Max Planck Institute)
An Efficient Semismooth Newton based Algorithm for Convex ClusteringYancheng Yuan (National University of Singapore) · Defeng Sun (The Chinese Hong Kong Polytechnic University) · Kim-Chuan Toh (National University of Singapre)
Least-Squares Temporal Difference Learning for the Linear Quadratic RegulatorStephen Tu (UC Berkeley) · Benjamin Recht (Berkeley)
The Multilinear Structure of ReLU NetworksThomas Laurent (Loyola Marymount University) · James von Brecht (CSULB)
Learning long term dependencies via Fourier recurrent unitsJiong Zhang (University of Texas at Austin) · Yibo Lin (UT-Austin) · Zhao Song (UT-Austin) · Inderjit Dhillon (UT Austin & Amazon)
Detecting non-causal artifacts in multivariate linear regression modelsDominik Janzing (Amazon Research Tübingen) · Bernhard Schölkopf (MPI for Intelligent Systems Tübingen, Germany)
Importance Weighted Transfer of Samples in Reinforcement LearningAndrea Tirinzoni (Politecnico di Milano) · Andrea Sessa (Politecnico di Milano) · Matteo Pirotta (SequeL - Inria Lille - Nord Europe) · Marcello Restelli (Politecnico di Milano)
On Discrete-Continuous Mixtures in Probabilistic Programming: the Extended Semantics and General Inference AlgorithmsYi Wu (UC Berkeley) · Siddharth Srivastava (Arizona State University) · Nicholas Hay () · Simon Du (Carnegie Mellon University) · Stuart Russell (UC Berkeley)
SADAGRAD: Strongly Adaptive Stochastic Gradient MethodsZaiyi Chen (University of Science and Technology of China) · Yi Xu (The University of Iowa) · Enhong Chen (University of Science and Technology of China) · Tianbao Yang (The University of Iowa)
Optimization Landscape and Expressivity of Deep CNNsQuynh Nguyen (Saarland University) · Matthias Hein (University of Tuebingen)
Composite Functional Gradient Learning of Generative Adversarial ModelsRie Johnson (RJ Research Consulting) · Tong Zhang (Tecent AI Lab)
Learning Dynamics of Linear Denoising AutoencodersArnu Pretorius (Stellenbosch University) · Steve Kroon (Stellenbosch University) · Herman Kamper (Stellenbosch University)
Noise2Noise: Learning Image Restoration without Clean Training ImagesSamuli Laine (NVIDIA Research) · Timo Aila (NVIDIA Research) · Jaakko Lehtinen (Aalto University & NVIDIA) · Tero Karras (NVidia) · Jacob Munkberg (NVIDIA) · Jon Hasselgren (NVIDIA) · Miika Aittala (MIT)
Learning Localized Spatio-Temporal Models From Streaming DataMuhammad Osama (Uppsala University) · Dave Zachariah (Uppsala University) · Thomas Schön (Uppsala University)
A Simple Stochastic Variance Reduced Algorithm with Fast Convergence RatesKaiwen Zhou (The Chinese University of Hong Kong) · Fanhua Shang (The Chinese University of Hong Kong) · James Cheng (CUHK)
Katyusha X: Simple Momentum Method for Stochastic Sum-of-Nonconvex OptimizationZeyuan Allen-Zhu (Microsoft Research AI)
Clipped Action Policy GradientYasuhiro Fujita (Preferred Networks, Inc.) · Shin-ichi Maeda (Preferred Networks, inc.)
Revealing Common Behaviors in Heterogeneous PopulationsAndrey Zhitnikov (Technion) · Rotem Mulayoff (Technion) · Tomer Michaeli (Technion)
A probabilistic framework for multi-view feature learning with many-to-many associations via neural networksOkuno Akifumi (Kyoto University; RIKEN AIP) · Tetsuya Hada (Recruit Technologies Co. Ltd.) · Hidetoshi Shimodaira (Kyoto University / RIKEN AIP)
Curriculum Learning by Transfer Learning: Theory and Experiments with Deep NetworksDaphna Weinshall (Hebrew University of Jerusalem, Israel) · Gad Cohen (Hebrew University)
Faster Derivative-Free Stochastic Algorithm for Shared Memory MachinesBin Gu (University of Pittsburgh) · Zhouyuan Huo (University of Pittsburgh) · Heng Huang (University of Pittsburgh)
The Dynamics of Learning: A Random Matrix ApproachZhenyu Liao (L2S, CentraleSupelec) · Romain Couillet (CentralSupélec)
Stability and Generalization of Learning Algorithms that Converge to Global OptimaZachary Charles (University of Wisconsin-Madison) · Dimitris Papailiopoulos (ECE at University of Wisconsin-Madison)
GAIN: Missing Data Imputation using Generative Adversarial NetsJinsung Yoon (University of California, Los Angeles) · James Jordon (University of Oxford) · Mihaela van der Schaar (University of Oxford)
To Understand Deep Learning We Need to Understand Kernel LearningMikhail Belkin (Ohio State University) · Siyuan Ma (The Ohio State University) · Soumik Mandal ()
RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial NetworksJinsung Yoon (University of California, Los Angeles) · James Jordon (University of Oxford) · Mihaela van der Schaar (University of Oxford)
Fast Approximate Spectral Clustering for Dynamic NetworksLionel Martin (EPFL) · Andreas Loukas (EPFL) · Pierre Vandergheynst (École polytechnique fédérale de Lausanne)
Attention-based Deep Multiple Instance LearningMaximilian Ilse (University of Amsterdam) · Jakub Tomczak (University of Amsterdam) · Max Welling (University of Amsterdam)
The Mechanics of n-Player Differentiable GamesDavid Balduzzi (DeepMind) · Sebastien Racaniere (DeepMind) · James Martens (DeepMind) · Jakob Foerster (University of Oxford) · Karl Tuyls (Deepmind) · Thore Graepel (DeepMind)
**Weakly Submodular Maximization Beyond Cardinality Constraints: Does Randomization Help Greedy?**Lin Chen (Yale University) · Moran Feldman (The Open University of Israel) · Amin Karbasi (Yale)
Spotlight: Optimizing Device Placement for Training Deep Neural NetworksYuanxiang Gao (University of Toronto) · Department of Electrical and Computer Li Chen (Department of Electrical and Computer Engineering, University of Toronto) · Baochun Li (University of Toronto)
Spurious Local Minima are Common in Two-Layer ReLU Neural NetworksItay Safran (Weizmann Institute of Science) · Ohad Shamir (Weizmann Institute of Science)
Black-box Variational Inference for Stochastic Differential EquationsTom Ryder (Newcastle University) · Andrew Golightly (Newcastle University) · Stephen McGough (Newcastle University) · Dennis Prangle (Newcastle University)
Approximation Algorithms for Cascading Prediction ModelsMatthew Streeter (Google)
Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement LearningRonan Fruit (Inria Lille Nord-Europe) · Matteo Pirotta (SequeL - Inria Lille - Nord Europe) · Alessandro Lazaric (FAIR) · Ronald Ortner (Montanuniversitaet Leoben)
Nonconvex Optimization for Fair RegressionJunpei Komiyama (U-Tokyo) · Akiko Takeda (The Institute of Statistical Mathematics) · Junya Honda (University of Tokyo / RIKEN) · Hajime Shimao (Purdue University)
Stabilizing Gradients for Deep Neural Networks via Efficient SVD ParameterizationJiong Zhang (University of Texas at Austin) · Qi Lei (University of Texas at Austin) · Inderjit Dhillon (UT Austin & Amazon)
Bayesian Uncertainty Estimation for Batch Normalized Deep NetworksMattias Teye (Electronic Arts) · Hossein Azizpour (KTH) · Kevin Smith (KTH Royal Institute of Technology)
由于微信字数限制，部分文章信息没有展示，详情请查看：
https://icml.cc/Conferences/2018/AcceptedPapersInitial
【来源： 腾讯云开发者社区】
【作者： 新智元】
【原文链接】 https://cloud.tencent.com/developer/article/1138620
声明：转载此文是出于传递更多信息之目的。若有来源标注错误或侵犯了您的合法权益，请作者持权属证明与本网联系，我们将及时更正、删除，谢谢。
