Table of Contents

• Multimodal Model-Agnostic Meta-Learning via Task-Aware ModulationRisto Vuorio, Shao-Hua Sun, Hexiang Hu, Joseph J. Lim. 1-12 [doi]
• ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language TasksJiasen Lu, Dhruv Batra, Devi Parikh, Stefan Lee. 13-23 [doi]
• Stochastic Shared Embeddings: Data-driven Regularization of Embedding LayersLiwei Wu, Shuqing Li, Cho-Jui Hsieh, James L. Sharpnack. 24-34 [doi]
• Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular VideoJiawang Bian, Zhichao Li, Naiyan Wang, Huangying Zhan, Chunhua Shen, Ming-Ming Cheng, Ian D. Reid 0001. 35-45 [doi]
• Zero-shot Learning via Simultaneous Generating and LearningHyeonwoo Yu, Beomhee Lee. 46-56 [doi]
• Ask not what AI can do, but what AI should do: Towards a framework of task delegabilityBrian Lubars, Chenhao Tan. 57-67 [doi]
• Stand-Alone Self-Attention in Vision ModelsNiki Parmar, Prajit Ramachandran, Ashish Vaswani, Irwan Bello, Anselm Levskaya, Jon Shlens. 68-80 [doi]
• High Fidelity Video Prediction with Large Stochastic Recurrent Neural NetworksRuben Villegas, Arkanath Pathak, Harini Kannan, Dumitru Erhan, Quoc V. Le, Honglak Lee. 81-91 [doi]
• Unsupervised learning of object structure and dynamics from videosMatthias Minderer, Chen Sun, Ruben Villegas, Forrester Cole, Kevin P. Murphy, Honglak Lee. 92-102 [doi]
• GPipe: Efficient Training of Giant Neural Networks using Pipeline ParallelismYanping Huang, Youlong Cheng, Ankur Bapna, Orhan Firat, Dehao Chen, Mia Xu Chen, HyoukJoong Lee, Jiquan Ngiam, Quoc V. Le, Yonghui Wu, Zhifeng Chen. 103-112 [doi]
• Meta-Learning with Implicit GradientsAravind Rajeswaran, Chelsea Finn, Sham M. Kakade, Sergey Levine. 113-124 [doi]
• Adversarial Examples Are Not Bugs, They Are FeaturesAndrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry. 125-136 [doi]
• Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention NetworksVineet Kosaraju, Amir Sadeghian, Roberto Martín-Martín, Ian D. Reid 0001, Hamid Rezatofighi, Silvio Savarese. 137-146 [doi]
• FreeAnchor: Learning to Match Anchors for Visual Object DetectionXiaosong Zhang, Fang Wan, Chang Liu, Rongrong Ji, Qixiang Ye. 147-155 [doi]
• Private Hypothesis SelectionMark Bun, Gautam Kamath 0001, Thomas Steinke, Steven Z. Wu. 156-167 [doi]
• Differentially Private Algorithms for Learning Mixtures of Separated GaussiansGautam Kamath 0001, Or Sheffet, Vikrant Singhal, Jonathan Ullman. 168-180 [doi]
• Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean EstimationMark Bun, Thomas Steinke. 181-191 [doi]
• Multi-Resolution Weak Supervision for Sequential DataParoma Varma, Frederic Sala, Shiori Sagawa, Jason Alan Fries, Daniel Y. Fu, Saelig Khattar, Ashwini Ramamoorthy, Ke Xiao, Kayvon Fatahalian, James Priest, Christopher Ré. 192-203 [doi]
• DeepUSPS: Deep Robust Unsupervised Saliency Prediction via Self-supervisionDuc Tam Nguyen, Maximilian Dax, Chaithanya Kumar Mummadi, Thi-Phuong-Nhung Ngo, Thi Hoai Phuong Nguyen, Zhongyu Lou, Thomas Brox. 204-214 [doi]
• The Point Where Reality Meets Fantasy: Mixed Adversarial Generators for Image Splice DetectionVladimir V. Kniaz, Vladimir A. Knyaz, Fabio Remondino. 215-226 [doi]
• You Only Propagate Once: Accelerating Adversarial Training via Maximal PrincipleDinghuai Zhang, Tianyuan Zhang, Yiping Lu, Zhanxing Zhu, Bin Dong 0001. 227-238 [doi]
• Imitation Learning from Observations by Minimizing Inverse Dynamics DisagreementChao Yang, Xiaojian Ma, Wenbing Huang, Fuchun Sun, Huaping Liu 0001, JunZhou Huang, Chuang Gan. 239-249 [doi]
• Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein DistanceKimia Nadjahi, Alain Durmus, Umut Simsekli, Roland Badeau. 250-260 [doi]
• Generalized Sliced Wasserstein DistancesSoheil Kolouri, Kimia Nadjahi, Umut Simsekli, Roland Badeau, Gustavo K. Rohde. 261-272 [doi]
• First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient NoiseThanh Huy Nguyen, Umut Simsekli, Mert Gürbüzbalaban, Gaël Richard. 273-283 [doi]
• Blind Super-Resolution Kernel Estimation using an Internal-GANSefi Bell-Kligler, Assaf Shocher, Michal Irani. 284-293 [doi]
• Noise-tolerant fair classificationAlexandre Louis Lamy, Ziyuan Zhong. 294-305 [doi]
• Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy ProtectionBingzhe Wu, Shiwan Zhao, Chaochao Chen, Haoyang Xu, Li Wang, Xiaolu Zhang, Guangyu Sun 0003, Jun Zhou. 306-316 [doi]
• Joint-task Self-supervised Learning for Temporal CorrespondenceXueting Li, Sifei Liu, Shalini De Mello, Xiaolong Wang, Jan Kautz, Ming-Hsuan Yang 0001. 317-327 [doi]
• Provable Gradient Variance Guarantees for Black-Box Variational InferenceJustin Domke. 328-337 [doi]
• Divide and Couple: Using Monte Carlo Variational Objectives for Posterior ApproximationJustin Domke, Daniel R. Sheldon. 338-347 [doi]
• Experience Replay for Continual LearningDavid Rolnick, Arun Ahuja, Jonathan Schwarz, Timothy P. Lillicrap, Gregory Wayne. 348-358 [doi]
• Deep ReLU Networks Have Surprisingly Few Activation PatternsBoris Hanin, David Rolnick. 359-368 [doi]
• Chasing Ghosts: Instruction Following as Bayesian State TrackingPeter Anderson, Ayush Shrivastava, Devi Parikh, Dhruv Batra, Stefan Lee. 369-379 [doi]
• Block Coordinate Regularization by DenoisingYu Sun 0022, Jiaming Liu, Ulugbek Kamilov. 380-390 [doi]
• Reducing Noise in GAN Training with Variance Reduced ExtragradientTatjana Chavdarova, Gauthier Gidel, François Fleuret, Simon Lacoste-Julien. 391-401 [doi]
• Learning Erdos-Renyi Random Graphs via Edge Detecting QueriesZihan Li, Matthias Fresacher, Jonathan Scarlett. 402-412 [doi]
• A Primal-Dual link between GANs and AutoencodersHisham Husain, Richard Nock, Robert C. Williamson. 413-422 [doi]
• muSSP: Efficient Min-cost Flow Algorithm for Multi-object TrackingCongchao Wang, Yizhi Wang, Yinxue Wang, Chiung-Ting Wu, Guoqiang Yu. 423-432 [doi]
• Category Anchor-Guided Unsupervised Domain Adaptation for Semantic SegmentationQiming Zhang, Jing Zhang, Wei Liu 0005, Dacheng Tao. 433-443 [doi]
• Invert to Learn to InvertPatrick Putzky, Max Welling. 444-454 [doi]
• Equitable Stable Matchings in Quadratic TimeNikolaos Tziavelis, Ioannis Giannakopoulos, Katerina Doka, Nectarios Koziris, Panagiotis Karras. 455-465 [doi]
• Zero-Shot Semantic SegmentationMaxime Bucher, Tuan-Hung Vu, Matthieu Cord, Patrick Pérez. 466-477 [doi]
• Metric Learning for Adversarial RobustnessChengzhi Mao, Ziyuan Zhong, Junfeng Yang, Carl Vondrick, Baishakhi Ray. 478-489 [doi]
• DISN: Deep Implicit Surface Network for High-quality Single-view 3D ReconstructionQiangeng Xu, Weiyue Wang, Duygu Ceylan, Radomír Mech, Ulrich Neumann. 490-500 [doi]
• Batched Multi-armed Bandits ProblemZijun Gao, Yanjun Han, Zhimei Ren, Zhengqing Zhou. 501-511 [doi]
• vGraph: A Generative Model for Joint Community Detection and Node Representation LearningFan-Yun Sun, Meng Qu, Jordan Hoffmann, Chin-Wei Huang, Jian Tang 0005. 512-522 [doi]
• Differentially Private Bayesian Linear RegressionGarrett Bernstein, Daniel R. Sheldon. 523-533 [doi]
• Semantic Conditioned Dynamic Modulation for Temporal Sentence Grounding in VideosYitian Yuan, Lin Ma, Jingwen Wang, Wei Liu, Wenwu Zhu 0001. 534-544 [doi]
• AGEM: Solving Linear Inverse Problems via Deep Priors and SamplingBichuan Guo, Yuxing Han, Jiangtao Wen. 545-556 [doi]
• CPM-Nets: Cross Partial Multi-View NetworksChangqing Zhang, Zongbo Han, yajie cui, Huazhu Fu, Joey Tianyi Zhou, Qinghua Hu. 557-567 [doi]
• Learning to Predict Layout-to-image Conditional Convolutions for Semantic Image SynthesisXihui Liu, Guojun Yin, Jing Shao, Xiaogang Wang 0001, Hongsheng Li. 568-578 [doi]
• Staying up to Date with Online Content Changes Using Reinforcement Learning for SchedulingAndrey Kolobov, Yuval Peres, Cheng Lu, Eric Joel Horvitz. 579-589 [doi]
• SySCD: A System-Aware Parallel Coordinate Descent AlgorithmNikolas Ioannou, Celestine Mendler-Dünner, Thomas P. Parnell. 590-600 [doi]
• Importance Weighted Hierarchical Variational InferenceArtem Sobolev, Dmitry P. Vetrov. 601-613 [doi]
• RSN: Randomized Subspace NewtonRobert M. Gower, Dmitry Kovalev, Felix Lieder, Peter Richtárik. 614-623 [doi]
• Trust Region-Guided Proximal Policy OptimizationYuhui Wang, Hao He, Xiaoyang Tan, Yaozhong Gan. 624-634 [doi]
• Adversarial Self-Defense for Cycle-Consistent GANsDina Bashkirova, Ben Usman, Kate Saenko. 635-645 [doi]
• Towards closing the gap between the theory and practice of SVRGOthmane Sebbouh, Nidham Gazagnadou, Samy Jelassi, Francis Bach, Robert M. Gower. 646-656 [doi]
• Uniform Error Bounds for Gaussian Process Regression with Application to Safe ControlArmin Lederer, Jonas Umlauft, Sandra Hirche. 657-667 [doi]
• ETNet: Error Transition Network for Arbitrary Style TransferChunjin Song, Zhijie Wu, Yang Zhou, Minglun Gong, Hui Huang 0004. 668-677 [doi]
• No Pressure! Addressing the Problem of Local Minima in Manifold Learning AlgorithmsMax Vladymyrov. 678-687 [doi]
• Deep Equilibrium ModelsShaojie Bai, J. Zico Kolter, Vladlen Koltun. 688-699 [doi]
• Saccader: Improving Accuracy of Hard Attention Models for VisionGamaleldin F. Elsayed, Simon Kornblith, Quoc V. Le. 700-712 [doi]
• Multiway clustering via tensor block modelsMiaoyan Wang, Yuchen Zeng. 713-723 [doi]
• Regret Minimization for Reinforcement Learning with Vectorial Feedback and Complex ObjectivesWang Chi Cheung. 724-734 [doi]
• NAT: Neural Architecture Transformer for Accurate and Compact ArchitecturesYong Guo, Yin Zheng, Mingkui Tan, Qi Chen, Jian Chen 0011, Peilin Zhao, JunZhou Huang. 735-747 [doi]
• Selecting Optimal Decisions via Distributionally Robust Nearest-Neighbor RegressionRuidi Chen, Ioannis Ch. Paschalidis. 748-758 [doi]
• Network Pruning via Transformable Architecture SearchXuanyi Dong, Yi Yang 0001. 759-770 [doi]
• Differentiable Cloth Simulation for Inverse ProblemsJunbang Liang, Ming C. Lin, Vladlen Koltun. 771-780 [doi]
• Poisson-Randomized Gamma Dynamical SystemsAaron Schein, Scott W. Linderman, Mingyuan Zhou, David M. Blei, Hanna M. Wallach. 781-792 [doi]
• Volumetric Correspondence Networks for Optical FlowGengshan Yang, Deva Ramanan. 793-803 [doi]
• Learning Conditional Deformable Templates with Convolutional NetworksAdrian V. Dalca, Marianne Rakic, John V. Guttag, Mert R. Sabuncu. 804-816 [doi]
• Fast Low-rank Metric Learning for Large-scale and High-dimensional DataHan Liu, Zhizhong Han, Yu-Shen Liu, Ming Gu 0001. 817-827 [doi]
• Efficient Symmetric Norm Regression via Linear SketchingZhao Song, Ruosong Wang, Lin Yang, Hongyang Zhang, Peilin Zhong. 828-838 [doi]
• RUBi: Reducing Unimodal Biases for Visual Question AnsweringRémi Cadène, Corentin Dancette, Hedi Ben-younes, Matthieu Cord, Devi Parikh. 839-850 [doi]
• Why Can't I Dance in the Mall? Learning to Mitigate Scene Bias in Action RecognitionJinwoo Choi, Chen Gao, Joseph C. E. Messou, Jia-Bin Huang. 851-863 [doi]
• NeurVPS: Neural Vanishing Point Scanning via Conic ConvolutionYichao Zhou, Haozhi Qi, Jingwei Huang, Yi Ma. 864-873 [doi]
• DATA: Differentiable ArchiTecture ApproximationJianlong Chang, Xinbang Zhang, Yiwen Guo, Gaofeng Meng, Shiming Xiang, Chunhong Pan. 874-884 [doi]
• Learn, Imagine and Create: Text-to-Image Generation from Prior KnowledgeTingting Qiao, Jing Zhang, Duanqing Xu, Dacheng Tao. 885-895 [doi]
• Memory-oriented Decoder for Light Field Salient Object DetectionMiao Zhang, Jingjing Li, Ji Wei, Yongri Piao, Huchuan Lu. 896-906 [doi]
• Multi-label Co-regularization for Semi-supervised Facial Action Unit RecognitionXuesong Niu, Hu Han, Shiguang Shan, Xilin Chen. 907-917 [doi]
• Correlated Uncertainty for Learning Dense Correspondences from Noisy LabelsNatalia Neverova, David Novotný, Andrea Vedaldi. 918-926 [doi]
• Powerset Convolutional Neural NetworksChris Wendler, Markus Püschel, Dan Alistarh. 927-938 [doi]
• Optimal Pricing in Repeated Posted-Price Auctions with Different Patience of the Seller and the BuyerArsenii Vanunts, Alexey Drutsa. 939-951 [doi]
• An Accelerated Decentralized Stochastic Proximal Algorithm for Finite SumsHadrien Hendrikx, Francis Bach, Laurent Massoulié. 952-962 [doi]
• Point-Voxel CNN for Efficient 3D Deep LearningZhijian Liu, Haotian Tang, Yujun Lin, Song Han. 963-973 [doi]
• Deep Learning without Weight TransportMohamed Akrout, Collin Wilson, Peter C. Humphreys, Timothy P. Lillicrap, Douglas B. Tweed. 974-982 [doi]
• Combinatorial Bandits with Relative FeedbackAadirupa Saha, Aditya Gopalan. 983-993 [doi]
• General Proximal Incremental Aggregated Gradient Algorithms: Better and Novel Results under General SchemeTao Sun, Yuejiao Sun, Dongsheng Li, Qing Liao 0001. 994-1004 [doi]
• A Condition Number for Joint Optimization of Cycle-Consistent NetworksLeonidas J. Guibas, Qixing Huang, Zhenxiao Liang. 1005-1015 [doi]
• Explicit Disentanglement of Appearance and Perspective in Generative ModelsNicki Skafte Detlefsen, Søren Hauberg. 1016-1026 [doi]
• Polynomial Cost of Adaptation for X-Armed BanditsHédi Hadiji. 1027-1036 [doi]
• Learning to Propagate for Graph Meta-LearningLu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang. 1037-1048 [doi]
• Secretary Ranking with Minimal InversionsSepehr Assadi, Eric Balkanski, Renato Paes Leme. 1049-1061 [doi]
• Nonparametric Regressive Point Processes Based on Conditional Gaussian ProcessesSiqi Liu, Milos Hauskrecht. 1062-1072 [doi]
• Learning Perceptual Inference by ContrastingChi Zhang, Baoxiong Jia, Feng Gao, Yixin Zhu, Hongjing Lu, Song Chun Zhu. 1073-1085 [doi]
• Selecting the independent coordinates of manifolds with large aspect ratiosYu-Chia Chen, Marina Meila. 1086-1095 [doi]
• Region-specific Diffeomorphic Metric MappingZhengyang Shen, François-Xavier Vialard, Marc Niethammer. 1096-1106 [doi]
• Deep Supervised Summarization: Algorithm and Application to Learning InstructionsChengguang Xu, Ehsan Elhamifar. 1107-1118 [doi]
• Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene RepresentationsVincent Sitzmann, Michael Zollhöfer, Gordon Wetzstein. 1119-1130 [doi]
• Reconciling λ-Returns with Experience ReplayBrett Daley, Christopher Amato. 1131-1140 [doi]
• Control Batch Size and Learning Rate to Generalize Well: Theoretical and Empirical EvidenceFengxiang He, Tongliang Liu, Dacheng Tao. 1141-1150 [doi]
• Non-Asymptotic Gap-Dependent Regret Bounds for Tabular MDPsMax Simchowitz, Kevin G. Jamieson. 1151-1160 [doi]
• A Graph Theoretic Framework of Recomputation Algorithms for Memory-Efficient BackpropagationMitsuru Kusumoto, Takuya Inoue, Gentaro Watanabe, Takuya Akiba, Masanori Koyama. 1161-1170 [doi]
• Combinatorial Inference against Label NoisePaul Hongsuck Seo, Geeho Kim, Bohyung Han. 1171-1181 [doi]
• Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement LearningChao Qu, Shie Mannor, Huan Xu, Yuan Qi, Le Song, Junwu Xiong. 1182-1191 [doi]
• Convolution with even-sized kernels and symmetric paddingShuang Wu, Guanrui Wang, Pei Tang, Feng Chen, Luping Shi. 1192-1203 [doi]
• On The Classification-Distortion-Perception TradeoffDong Liu, Haochen Zhang, Zhiwei Xiong. 1204-1213 [doi]
• Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-UpDominic Richards, Patrick Rebeschini. 1214-1225 [doi]
• Online sampling from log-concave distributionsHolden Lee, Oren Mangoubi, Nisheeth K. Vishnoi. 1226-1237 [doi]
• Envy-Free ClassificationMaria-Florina Balcan, Travis Dick, Ritesh Noothigattu, Ariel D. Procaccia. 1238-1248 [doi]
• Finding Friend and Foe in Multi-Agent GamesJack Serrino, Max Kleiman-Weiner, David C. Parkes, Josh Tenenbaum. 1249-1259 [doi]
• Image Synthesis with a Single (Robust) ClassifierShibani Santurkar, Andrew Ilyas, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry. 1260-1271 [doi]
• Model Compression with Adversarial Robustness: A Unified Optimization FrameworkShupeng Gui, Haotao Wang, Haichuan Yang, Chen Yu, Zhangyang Wang, Ji Liu 0002. 1283-1294 [doi]
• Cross-channel Communication NetworksJianwei Yang, Zhile Ren, Chuang Gan, Hongyuan Zhu, Devi Parikh. 1295-1304 [doi]
• CondConv: Conditionally Parameterized Convolutions for Efficient InferenceBrandon Yang, Gabriel Bender, Quoc V. Le, Jiquan Ngiam. 1305-1316 [doi]
• Regression Planning NetworksDanfei Xu, Roberto Martín-Martín, De-An Huang, Yuke Zhu, Silvio Savarese, Li F. Fei-Fei. 1317-1327 [doi]
• Twin Auxilary Classifiers GANMingming Gong, Yanwu Xu, Chunyuan Li, Kun Zhang 0001, Kayhan Batmanghelich. 1328-1337 [doi]
• Conditional Structure Generation through Graph Variational Generative Adversarial NetsCarl Yang, Peiye Zhuang, Wenhan Shi, Alan Luu, Pan Li 0005. 1338-1349 [doi]
• Distributional Policy Optimization: An Alternative Approach for Continuous ControlChen Tessler, Guy Tennenholtz, Shie Mannor. 1350-1360 [doi]
• Sampling Sketches for Concave Sublinear Functions of FrequenciesEdith Cohen, Ofir Geri. 1361-1371 [doi]
• Deliberative Explanations: visualizing network insecuritiesPei Wang, Nuno Nasconcelos. 1372-1383 [doi]
• Computing Full Conformal Prediction Set with Approximate HomotopyEugène Ndiaye, Ichiro Takeuchi. 1384-1393 [doi]
• Failing Loudly: An Empirical Study of Methods for Detecting Dataset ShiftStephan Rabanser, Stephan Günnemann, Zachary C. Lipton. 1394-1406 [doi]
• Hierarchical Reinforcement Learning with Advantage-Based Auxiliary RewardsSiyuan Li, Rui Wang, Minxue Tang, Chongjie Zhang. 1407-1417 [doi]
• Multi-View Reinforcement LearningMinne Li, Lisheng Wu, Jun Wang 0012, Haitham Bou-Ammar. 1418-1429 [doi]
• Cascade RPN: Delving into High-Quality Region Proposal Network with Adaptive ConvolutionThang Vu, Hyunjun Jang, Trung X. Pham, Chang Dong Yoo. 1430-1440 [doi]
• Neural Diffusion Distance for Image SegmentationJian Sun 0009, ZongBen Xu. 1441-1451 [doi]
• Fine-grained Optimization of Deep Neural NetworksMete Ozay. 1452-1462 [doi]
• Extending Stein's unbiased risk estimator to train deep denoisers with correlated pairs of noisy imagesMagauiya Zhussip, Shakarim Soltanayev, Se Young Chun. 1463-1473 [doi]
• Fixing Implicit Derivatives: Trust-Region Based Learning of Continuous Energy FunctionsChris Russell 0001, Matteo Toso, Neill Campbell. 1474-1484 [doi]
• Hyperspherical Prototype NetworksPascal Mettes, Elise van der Pol, Cees Snoek. 1485-1495 [doi]
• Expressive power of tensor-network factorizations for probabilistic modelingIvan Glasser, Ryan Sweke, Nicola Pancotti, Jens Eisert, J. Ignacio Cirac. 1496-1508 [doi]
• HyperGCN: A New Method For Training Graph Convolutional Networks on HypergraphsNaganand Yadati, Madhav Nimishakavi, Prateek Yadav, Vikram Nitin, Anand Louis, Partha P. Talukdar. 1509-1520 [doi]
• SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle PointsZhize Li. 1521-1531 [doi]
• Efficient Meta Learning via Minibatch Proximal UpdatePan Zhou, Xiaotong Yuan, Huan Xu, Shuicheng Yan, Jiashi Feng. 1532-1542 [doi]
• Unconstrained Monotonic Neural NetworksAntoine Wehenkel, Gilles Louppe. 1543-1553 [doi]
• Guided Similarity Separation for Image RetrievalChundi Liu, Guang Wei Yu, Maksims Volkovs, Cheng Chang, Himanshu Rai, Junwei Ma, Satya Krishna Gorti. 1554-1564 [doi]
• Learning Imbalanced Datasets with Label-Distribution-Aware Margin LossKaidi Cao, Colin Wei, Adrien Gaidon, Nikos Aréchiga, Tengyu Ma. 1565-1576 [doi]
• Strategizing against No-regret LearnersYuan Deng, Jon Schneider, Balasubramanian Sivan. 1577-1585 [doi]
• D-VAE: A Variational Autoencoder for Directed Acyclic GraphsMuhan Zhang, Shali Jiang, Zhicheng Cui, Roman Garnett, Yixin Chen. 1586-1598 [doi]
• Hierarchical Optimal Transport for Document RepresentationMikhail Yurochkin, Sebastian Claici, Edward Chien, Farzaneh Mirzazadeh, Justin M. Solomon. 1599-1609 [doi]
• Multivariate Sparse Coding of Nonstationary Covariances with Gaussian ProcessesRui Li. 1610-1619 [doi]
• Positional NormalizationBoyi Li, Felix Wu, Kilian Q. Weinberger, Serge J. Belongie. 1620-1632 [doi]
• A New Defense Against Adversarial Images: Turning a Weakness into a StrengthShengyuan Hu, Tao Yu, Chuan Guo, Wei-Lun Chao, Kilian Q. Weinberger. 1633-1644 [doi]
• Quadratic Video InterpolationXiangyu Xu, Li Si-Yao, Wenxiu Sun, Qian Yin, Ming-Hsuan Yang 0001. 1645-1654 [doi]
• ResNets Ensemble via the Feynman-Kac Formalism to Improve Natural and Robust AccuraciesBao Wang, Zuoqiang Shi, Stanley J. Osher. 1655-1665 [doi]
• Incremental Scene SynthesisBenjamin Planche, Xuejian Rong, Ziyan Wu, Srikrishna Karanam, Harald Kosch, Yingli Tian, Jan Ernst, Andreas Hutter. 1666-1676 [doi]
• Self-Supervised Generalisation with Meta Auxiliary LearningShikun Liu, Andrew J. Davison, Edward Johns. 1677-1687 [doi]
• Variational Denoising Network: Toward Blind Noise Modeling and RemovalZongsheng Yue, Hongwei Yong, Qian Zhao, Deyu Meng, Lei Zhang 0006. 1688-1699 [doi]
• Fast Sparse Group LassoYasutoshi Ida, Yasuhiro Fujiwara, Hisashi Kashima. 1700-1708 [doi]
• Learnable Tree Filter for Structure-preserving Feature TransformLin Song, Yanwei Li, Zeming Li, Gang Yu, Hongbin Sun 0001, Jian Sun 0015, Nanning Zheng. 1709-1719 [doi]
• Data-Dependence of Plateau Phenomenon in Learning with Neural Network - Statistical Mechanical AnalysisYuki Yoshida, Masato Okada. 1720-1728 [doi]
• Coordinated hippocampal-entorhinal replay as structural inferenceTalfan Evans, Neil Burgess. 1729-1741 [doi]
• Cascaded Dilated Dense Network with Two-step Data Consistency for MRI ReconstructionHao Zheng, Faming Fang, Guixu Zhang. 1742-1752 [doi]
• On the Ineffectiveness of Variance Reduced Optimization for Deep LearningAaron Defazio, Léon Bottou. 1753-1763 [doi]
• On the Curved Geometry of Accelerated OptimizationAaron Defazio. 1764-1773 [doi]
• Multi-marginal Wasserstein GANJiezhang Cao, Langyuan Mo, Yifan Zhang 0004, Kui Jia, Chunhua Shen, Mingkui Tan. 1774-1784 [doi]
• Better Exploration with Optimistic Actor CriticKamil Ciosek, Quan Vuong, Robert Loftin, Katja Hofmann. 1785-1796 [doi]
• Importance Resampling for Off-policy PredictionMatthew Schlegel, Wesley Chung, Daniel Graves, Jian Qian, Martha White. 1797-1807 [doi]
• The Label Complexity of Active Learning from Observational DataSongbai Yan, Kamalika Chaudhuri, Tara Javidi. 1808-1817 [doi]
• Meta-Learning Representations for Continual LearningKhurram Javed, Martha White. 1818-1828 [doi]
• Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial TrainingHaichao Zhang, Jianyu Wang. 1829-1839 [doi]
• Visualizing the PHATE of Neural NetworksScott Gigante, Adam S. Charles, Smita Krishnaswamy, Gal Mishne. 1840-1851 [doi]
• The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiersAlex X. Lu, Amy X. Lu, Wiebke Schormann, Marzyeh Ghassemi, David W. Andrews, Alan M. Moses. 1852-1860 [doi]
• Nonconvex Low-Rank Tensor Completion from Noisy DataChangxiao Cai, Gen Li, H. Vincent Poor, Yuxin Chen 0002. 1861-1872 [doi]
• Beyond Online Balanced Descent: An Optimal Algorithm for Smoothed Online OptimizationGautam Goel, Yiheng Lin, Haoyuan Sun, Adam Wierman. 1873-1883 [doi]
• Channel Gating Neural NetworksWeizhe Hua, Yuan Zhou, Christopher De Sa, Zhiru Zhang, G. Edward Suh. 1884-1894 [doi]
• Neural networks grown and self-organized by noiseGuruprasad Raghavan, Matt Thomson. 1895-1905 [doi]
• Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer LearningXinyang Chen, Sinan Wang, Bo Fu, Mingsheng Long, Jianmin Wang. 1906-1916 [doi]
• Meta-Weight-Net: Learning an Explicit Mapping For Sample WeightingJun Shu, Qi Xie, Lixuan Yi, Qian Zhao 0002, Sanping Zhou, ZongBen Xu, Deyu Meng. 1917-1928 [doi]
• Variational Structured Semantic Inference for Diverse Image CaptioningFuhai Chen, Rongrong Ji, Jiayi Ji, Xiaoshuai Sun, Baochang Zhang, Xuri Ge, Yongjian Wu, Feiyue Huang, Yan Wang. 1929-1939 [doi]
• Mapping State Space using Landmarks for Universal Goal ReachingZhiao Huang, Fangchen Liu, Hao Su. 1940-1950 [doi]
• Transferable Normalization: Towards Improving Transferability of Deep Neural NetworksXimei Wang, Ying Jin, Mingsheng Long, Jianmin Wang, Michael I. Jordan. 1951-1961 [doi]
• Random deep neural networks are biased towards simple functionsGiacomo De Palma, Bobak Toussi Kiani, Seth Lloyd. 1962-1974 [doi]
• XNAS: Neural Architecture Search with Expert AdviceNiv Nayman, Asaf Noy, Tal Ridnik, Itamar Friedman, Rong Jin, Lihi Zelnik-Manor. 1975-1985 [doi]
• 2: Viewpoint Generalization via a Binocular VisionWei-Da Chen, Shan-Hung Wu. 1986-1998 [doi]
• Generalized Off-Policy Actor-CriticShangtong Zhang, Wendelin Boehmer, Shimon Whiteson. 1999-2009 [doi]
• DAC: The Double Actor-Critic Architecture for Learning OptionsShangtong Zhang, Shimon Whiteson. 2010-2020 [doi]
• Numerically Accurate Hyperbolic Embeddings Using Tiling-Based ModelsTao Yu, Christopher De Sa. 2021-2031 [doi]
• Controlling Neural Level SetsMatan Atzmon, Niv Haim, Lior Yariv, Ofer Israelov, Haggai Maron, Yaron Lipman. 2032-2041 [doi]
• Blended Matching PursuitCyrille W. Combettes, Sebastian Pokutta. 2042-2052 [doi]
• An Improved Analysis of Training Over-parameterized Deep Neural NetworksDifan Zou, Quanquan Gu. 2053-2062 [doi]
• Controllable Text-to-Image GenerationBowen Li, Xiaojuan Qi, Thomas Lukasiewicz, Philip H. S. Torr. 2063-2073 [doi]
• Improving Textual Network Learning with Variational Homophilic EmbeddingsWenlin Wang, Chenyang Tao, Zhe Gan, Guoyin Wang, Liqun Chen, Xinyuan Zhang, Ruiyi Zhang, Qian Yang, Ricardo Henao, Lawrence Carin. 2074-2085 [doi]
• Rethinking Generative Mode Coverage: A Pointwise Guaranteed ApproachPeilin Zhong, Yuchen Mo, Chang Xiao, Pengyu Chen, Changxi Zheng. 2086-2097 [doi]
• The Randomized Midpoint Method for Log-Concave SamplingRuoqi Shen, Yin Tat Lee. 2098-2109 [doi]
• Sample-Efficient Deep Reinforcement Learning via Episodic Backward UpdateSu-Young Lee, SungIk Choi, Sae-Young Chung. 2110-2119 [doi]
• Fully Neural Network based Model for General Temporal Point ProcessesTakahiro Omi, Naonori Ueda, Kazuyuki Aihara. 2120-2129 [doi]
• Gate Decorator: Global Filter Pruning Method for Accelerating Deep Convolutional Neural NetworksZhonghui You, Kun Yan, Jinmian Ye, Meng Ma, Ping Wang 0003. 2130-2141 [doi]
• Discrimination in Online Markets: Effects of Social Bias on Learning from Reviews and Policy DesignFaidra Georgia Monachou, Itai Ashlagi. 2142-2152 [doi]
• Provably Powerful Graph NetworksHaggai Maron, Heli Ben Hamu, Hadar Serviansky, Yaron Lipman. 2153-2164 [doi]
• Order Optimal One-Shot Distributed LearningArsalan Sharif-Nassab, Saber Salehkaleybar, S. Jamaloddin Golestani. 2165-2174 [doi]
• Information Competing Process for Learning Diversified RepresentationsJie Hu, Rongrong Ji, Shengchuan Zhang, Xiaoshuai Sun, Qixiang Ye, Chia-Wen Lin, Qi Tian 0002. 2175-2186 [doi]
• GENO - GENeric Optimization for Classical Machine LearningSören Laue, Matthias Mitterreiter, Joachim Giesen. 2187-2198 [doi]
• Conditional Independence Testing using Generative Adversarial NetworksAlexis Bellot, Mihaela van der Schaar. 2199-2208 [doi]
• Online Stochastic Shortest Path with Bandit Feedback and Unknown Transition FunctionAviv Rosenberg 0002, Yishay Mansour. 2209-2218 [doi]
• Partitioning Structure Learning for Segmented Linear Regression TreesXiangyu Zheng, Song Xi Chen. 2219-2228 [doi]
• A Tensorized Transformer for Language ModelingXindian Ma, Peng Zhang, Shuai Zhang, Nan Duan, Yuexian Hou, Ming Zhou, Dawei Song 0001. 2229-2239 [doi]
• Kernel Stein Tests for Multiple Model ComparisonJen Ning Lim, Makoto Yamada, Bernhard Schölkopf, Wittawat Jitkrittum. 2240-2250 [doi]
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• Rethinking the CSC Model for Natural ImagesDror Simon, Michael Elad. 2271-2281 [doi]
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• DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution CorrectionsOfir Nachum, Yinlam Chow, Bo Dai, Lihong Li 0001. 2315-2325 [doi]
• Hyper-Graph-Network Decoders for Block CodesEliya Nachmani, Lior Wolf. 2326-2336 [doi]
• Large Scale Markov Decision Processes with Changing RewardsAdrian Rivera Cardoso, He Wang, Huan Xu. 2337-2347 [doi]
• Multiview Aggregation for Learning Category-Specific Shape ReconstructionSrinath Sridhar 0002, Davis Rempe, Julien Valentin, Sofien Bouaziz, Leonidas J. Guibas. 2348-2359 [doi]
• Semi-Parametric Dynamic Contextual PricingVirag Shah, Ramesh Johari, Jose H. Blanchet. 2360-2370 [doi]
• Interlaced Greedy Algorithm for Maximization of Submodular Functions in Nearly Linear TimeAlan Kuhnle. 2371-2381 [doi]
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• Gradient Information for Representation and ModelingJie Ding, A. Robert Calderbank, Vahid Tarokh. 2393-2402 [doi]
• SpiderBoost and Momentum: Faster Variance Reduction AlgorithmsZhe Wang, Kaiyi Ji, Yi Zhou, Yingbin Liang, Vahid Tarokh. 2403-2413 [doi]
• Minimax Optimal Estimation of Approximate Differential Privacy on Neighboring DatabasesXiyang Liu, Sewoong Oh. 2414-2425 [doi]
• Backprop with Approximate Activations for Memory-efficient Network TrainingAyan Chakrabarti, Benjamin Moseley. 2426-2435 [doi]
• Training Image Estimators without Image Ground TruthZhihao Xia, Ayan Chakrabarti. 2436-2446 [doi]
• Deep Structured Prediction for Facial Landmark DetectionLisha Chen, Hui Su, Qiang Ji. 2447-2457 [doi]
• Information-Theoretic Confidence Bounds for Reinforcement LearningXiuyuan Lu, Benjamin Van Roy. 2458-2466 [doi]
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• Total Least Squares Regression in Input Sparsity TimeHuaian Diao, Zhao Song, David P. Woodruff, Xin Yang. 2478-2489 [doi]
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• Adapting Neural Networks for the Estimation of Treatment EffectsClaudia Shi, David M. Blei, Victor Veitch. 2503-2513 [doi]
• Learning Transferable Graph ExplorationHanjun Dai, Yujia Li, Chenglong Wang, Rishabh Singh, Po-Sen Huang, Pushmeet Kohli. 2514-2525 [doi]
• Conformal Prediction Under Covariate ShiftRyan J. Tibshirani, Rina Foygel Barber, Emmanuel J. Candès, Aaditya Ramdas. 2526-2536 [doi]
• Optimal Analysis of Subset-Selection Based L_p Low-Rank ApproximationChen Dan, Hong Wang, Hongyang Zhang, Yuchen Zhou, Pradeep Ravikumar. 2537-2548 [doi]
• Asymmetric Valleys: Beyond Sharp and Flat Local MinimaHaowei He, Gao Huang, Yang Yuan. 2549-2560 [doi]
• Positive-Unlabeled Compression on the CloudYixing Xu, Yunhe Wang, Hanting Chen, Kai Han, Chunjing Xu, Dacheng Tao, Chang Xu 0002. 2561-2570 [doi]
• Direct Estimation of Differential Functional Graphical ModelsBoxin Zhao, Y. Samuel Wang, Mladen Kolar. 2571-2581 [doi]
• On the Calibration of Multiclass Classification with RejectionChenri Ni, Nontawat Charoenphakdee, Junya Honda, Masashi Sugiyama. 2582-2592 [doi]
• Third-Person Visual Imitation Learning via Decoupled Hierarchical ControllerPratyusha Sharma, Deepak Pathak, Abhinav Gupta 0001. 2593-2603 [doi]
• Stagewise Training Accelerates Convergence of Testing Error Over SGDZhuoning Yuan, Yan Yan 0006, Rong Jin, Tianbao Yang. 2604-2614 [doi]
• Learning Robust Options by Conditional Value at Risk OptimizationTakuya Hiraoka, Takahisa Imagawa, Tatsuya Mori, Takashi Onishi, Yoshimasa Tsuruoka. 2615-2625 [doi]
• Non-asymptotic Analysis of Stochastic Methods for Non-Smooth Non-Convex Regularized ProblemsYi Xu, Rong Jin, Tianbao Yang. 2626-2636 [doi]
• On Learning Over-parameterized Neural Networks: A Functional Approximation PerspectiveLili Su, Pengkun Yang. 2637-2646 [doi]
• Drill-down: Interactive Retrieval of Complex Scenes using Natural Language QueriesFuwen Tan, Paola Cascante-Bonilla, Xiaoxiao Guo, Hui Wu, Song Feng, Vicente Ordonez. 2647-2657 [doi]
• Dual Variational Generation for Low Shot Heterogeneous Face RecognitionChaoyou Fu, Xiang Wu 0001, Yibo Hu, Huaibo Huang, Ran He. 2670-2679 [doi]
• Discovering Neural WiringsMitchell Wortsman, Ali Farhadi, Mohammad Rastegari. 2680-2690 [doi]
• On the Optimality of Perturbations in Stochastic and Adversarial Multi-armed Bandit ProblemsBaekjin Kim, Ambuj Tewari. 2691-2700 [doi]
• Knowledge Extraction with No Observable DataJaemin Yoo, Minyong Cho, Taebum Kim, U Kang. 2701-2710 [doi]
• PAC-Bayes under potentially heavy tailsMatthew Holland. 2711-2720 [doi]
• One-Shot Object Detection with Co-Attention and Co-ExcitationTing-I Hsieh, Yi-Chen Lo, Hwann-Tzong Chen, Tyng-Luh Liu. 2721-2730 [doi]
• Quaternion Knowledge Graph EmbeddingsShuai Zhang 0007, Yi Tay, Lina Yao, Qi Liu. 2731-2741 [doi]
• Glyce: Glyph-vectors for Chinese Character RepresentationsYuxian Meng, Wei Wu, Fei Wang, Xiaoya Li, Ping Nie, Fan Yin, Muyu Li, Qinghong Han, Xiaofei Sun, Jiwei Li. 2742-2753 [doi]
• Turbo Autoencoder: Deep learning based channel codes for point-to-point communication channelsYihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath. 2754-2764 [doi]
• Heterogeneous Graph Learning for Visual Commonsense ReasoningWeijiang Yu, Jingwen Zhou, Weihao Yu, Xiaodan Liang, Nong Xiao. 2765-2775 [doi]
• Probabilistic Watershed: Sampling all spanning forests for seeded segmentation and semi-supervised learningEnrique Fita Sanmartin, Sebastian Damrich, Fred A. Hamprecht. 2776-2787 [doi]
• Classification-by-Components: Probabilistic Modeling of Reasoning over a Set of ComponentsSascha Saralajew, Lars Holdijk, Maike Rees, Ebubekir Asan, Thomas Villmann. 2788-2799 [doi]
• Identifying Causal Effects via Context-specific Independence RelationsSanttu Tikka, Antti Hyttinen, Juha Karvanen. 2800-2810 [doi]
• Bridging Machine Learning and Logical Reasoning by Abductive LearningWang-Zhou Dai, Qiu-Ling Xu, Yang Yu 0001, Zhi-Hua Zhou. 2811-2822 [doi]
• Regret Minimization for Reinforcement Learning by Evaluating the Optimal Bias FunctionZihan Zhang, Xiangyang Ji. 2823-2832 [doi]
• On the Global Convergence of (Fast) Incremental Expectation Maximization MethodsBelhal Karimi, Hoi-To Wai, Eric Moulines, Marc Lavielle. 2833-2843 [doi]
• A Linearly Convergent Proximal Gradient Algorithm for Decentralized OptimizationSulaiman A. Alghunaim, Kun Yuan, Ali H. Sayed. 2844-2854 [doi]
• Regularizing Trajectory Optimization with Denoising AutoencodersRinu Boney, Norman Di Palo, Mathias Berglund, Alexander Ilin, Juho Kannala, Antti Rasmus, Harri Valpola. 2855-2865 [doi]
• Learning Hierarchical Priors in VAEsAlexej Klushyn, Nutan Chen, Richard Kurle, Botond Cseke, Patrick van der Smagt. 2866-2875 [doi]
• Epsilon-Best-Arm Identification in Pay-Per-Reward Multi-Armed BanditsSivan Sabato. 2876-2886 [doi]
• Safe Exploration for Interactive Machine LearningMatteo Turchetta, Felix Berkenkamp, Andreas Krause 0001. 2887-2897 [doi]
• Addressing Failure Prediction by Learning Model ConfidenceCharles Corbière, Nicolas Thome, Avner Bar-Hen, Matthieu Cord, Patrick Pérez. 2898-2909 [doi]
• Combinatorial Bayesian Optimization using the Graph Cartesian ProductChangYong Oh, Jakub M. Tomczak, Efstratios Gavves, Max Welling. 2910-2920 [doi]
• Fooling Neural Network Interpretations via Adversarial Model ManipulationJuyeon Heo, Sunghwan Joo, Taesup Moon. 2921-2932 [doi]
• On Lazy Training in Differentiable ProgrammingLénaïc Chizat, Edouard Oyallon, Francis Bach. 2933-2943 [doi]
• Quality Aware Generative Adversarial NetworksParimala Kancharla, Sumohana S. Channappayya. 2944-2954 [doi]
• Copula-like Variational InferenceMarcel Hirt, Petros Dellaportas, Alain Durmus. 2955-2967 [doi]
• Implicit Regularization for Optimal Sparse RecoveryTomas Vaskevicius, Varun Kanade, Patrick Rebeschini. 2968-2979 [doi]
• Locally Private Gaussian EstimationMatthew Joseph, Janardhan Kulkarni, Jieming Mao, Steven Z. Wu. 2980-2989 [doi]
• Multi-mapping Image-to-Image Translation via Learning DisentanglementXiaoming Yu, Yuanqi Chen, Shan Liu, Thomas H. Li, Ge Li. 2990-2999 [doi]
• Spatially Aggregated Gaussian Processes with Multivariate Areal OutputsYusuke Tanaka 0002, Toshiyuki Tanaka, Tomoharu Iwata, Takeshi Kurashima, Maya Okawa, Yasunori Akagi, Hiroyuki Toda. 3000-3010 [doi]
• Fast Structured Decoding for Sequence ModelsZhiqing Sun, Zhuohan Li, Haoqing Wang, Di He, Zi Lin, Zhi-Hong Deng. 3011-3020 [doi]
• Learning Temporal Pose Estimation from Sparsely-Labeled VideosGedas Bertasius, Christoph Feichtenhofer, Du Tran, Jianbo Shi, Lorenzo Torresani. 3021-3032 [doi]
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• Real-Time Reinforcement LearningSimon Ramstedt, Chris Pal. 3067-3076 [doi]
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• SCAN: A Scalable Neural Networks Framework Towards Compact and Efficient ModelsLinfeng Zhang, Zhanhong Tan, Jiebo Song, Jingwei Chen, Chenglong Bao, Kaisheng Ma. 4029-4038 [doi]
• Revisiting the Bethe-Hessian: Improved Community Detection in Sparse Heterogeneous GraphsLorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay. 4039-4049 [doi]
• Teaching Multiple Concepts to a Forgetful LearnerAnette Hunziker, Yuxin Chen 0001, Oisin Mac Aodha, Manuel Gomez-Rodriguez, Andreas Krause 0001, Pietro Perona, Yisong Yue, Adish Singla. 4050-4060 [doi]
• Regularized Weighted Low Rank ApproximationFrank Ban, David P. Woodruff, Richard Zhang. 4061-4071 [doi]
• Practical and Consistent Estimation of f-DivergencesPaul K. Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya O. Tolstikhin. 4072-4082 [doi]
• Approximation Ratios of Graph Neural Networks for Combinatorial ProblemsRyoma Sato, Makoto Yamada, Hisashi Kashima. 4083-4092 [doi]
• Thinning for Accelerating the Learning of Point ProcessesTianbo Li, Yiping Ke. 4093-4103 [doi]
• A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative ModelsMaxim Kuznetsov, Daniil Polykovskiy, Dmitry P. Vetrov, Alexander Zhebrak. 4104-4114 [doi]
• Differentially Private Markov Chain Monte CarloMikko A. Heikkilä, Joonas Jälkö, Onur Dikmen, Antti Honkela. 4115-4125 [doi]
• Full-Gradient Representation for Neural Network VisualizationSuraj Srinivas, François Fleuret. 4126-4135 [doi]
• q-means: A quantum algorithm for unsupervised machine learningIordanis Kerenidis, Jonas Landman, Alessandro Luongo, Anupam Prakash. 4136-4146 [doi]
• Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and ConstraintsSebastian Tschiatschek, Ahana Ghosh, Luis Haug, Rati Devidze, Adish Singla. 4147-4157 [doi]
• Limitations of the empirical Fisher approximation for natural gradient descentFrederik Kunstner, Philipp Hennig, Lukas Balles. 4158-4169 [doi]
• Flow-based Image-to-Image Translation with Feature DisentanglementRuho Kondo, Keisuke Kawano, Satoshi Koide, Takuro Kutsuna. 4170-4180 [doi]
• Learning dynamic polynomial proofsAlhussein Fawzi, Mateusz Malinowski, Hamza Fawzi, Omar Fawzi. 4181-4190 [doi]
• Shape and Time Distortion Loss for Training Deep Time Series Forecasting ModelsVincent Le Guen, Nicolas Thome. 4191-4203 [doi]
• Understanding Attention and Generalization in Graph Neural NetworksBoris Knyazev, Graham W. Taylor, Mohamed R. Amer. 4204-4214 [doi]
• Data Cleansing for Models Trained with SGDSatoshi Hara, Atsushi Nitanda, Takanori Maehara. 4215-4224 [doi]
• Curvilinear Distance Metric LearningShuo Chen 0003, Lei Luo, Jian Yang 0003, Chen Gong 0002, Jun Li, Heng Huang. 4225-4234 [doi]
• Embedding Symbolic Knowledge into Deep NetworksYaqi Xie, Ziwei Xu, Kuldeep Meel, Mohan S. Kankanhalli, Harold Soh. 4235-4245 [doi]
• Modeling Uncertainty by Learning a Hierarchy of Deep Neural ConnectionsRaanan Y. Yehezkel Rohekar, Yaniv Gurwicz, Shami Nisimov, Gal Novik. 4246-4256 [doi]
• Efficient Graph Generation with Graph Recurrent Attention NetworksRenjie Liao, Yujia Li, Yang Song, Shenlong Wang, William L. Hamilton, David Duvenaud, Raquel Urtasun, Richard S. Zemel. 4257-4267 [doi]
• Beyond Alternating Updates for Matrix Factorization with Inertial Bregman Proximal Gradient AlgorithmsMahesh Chandra Mukkamala, Peter Ochs. 4268-4278 [doi]
• Learning Deep Bilinear Transformation for Fine-grained Image RepresentationHeliang Zheng, Jianlong Fu, Zheng-Jun Zha, Jiebo Luo. 4279-4288 [doi]
• Practical Deep Learning with Bayesian PrinciplesKazuki Osawa, Siddharth Swaroop, Mohammad Emtiyaz Khan, Anirudh Jain, Runa Eschenhagen, Richard E. Turner, Rio Yokota. 4289-4301 [doi]
• Training Language GANs from ScratchCyprien de Masson d'Autume, Shakir Mohamed, Mihaela Rosca, Jack W. Rae. 4302-4313 [doi]
• Pseudo-Extended Markov chain Monte CarloChristopher Nemeth, Fredrik Lindsten, Maurizio Filippone, James Hensman. 4314-4324 [doi]
• Differentially Private Bagging: Improved utility and cheaper privacy than subsample-and-aggregateJames Jordon, Jinsung Yoon, Mihaela van der Schaar. 4325-4334 [doi]
• Propagating Uncertainty in Reinforcement Learning via Wasserstein BarycentersAlberto Maria Metelli, Amarildo Likmeta, Marcello Restelli. 4335-4347 [doi]
• On Adversarial Mixup ResynthesisChristopher Beckham, Sina Honari, Vikas Verma, Alex Lamb, Farnoosh Ghadiri, R. Devon Hjelm, Yoshua Bengio, Chris Pal. 4348-4359 [doi]
• A Geometric Perspective on Optimal Representations for Reinforcement LearningMarc G. Bellemare, Will Dabney, Robert Dadashi, Adrien Ali Taïga, Pablo Samuel Castro, Nicolas Le Roux, Dale Schuurmans, Tor Lattimore, Clare Lyle. 4360-4371 [doi]
• Learning New Tricks From Old Dogs: Multi-Source Transfer Learning From Pre-Trained NetworksJoshua Lee, Prasanna Sattigeri, Gregory W. Wornell. 4372-4382 [doi]
• Understanding and Improving Layer NormalizationJingjing Xu, Xu Sun 0001, Zhiyuan Zhang, Guangxiang Zhao, Junyang Lin. 4383-4393 [doi]
• Uncertainty-based Continual Learning with Adaptive RegularizationHongjoon Ahn, Sungmin Cha, Donggyu Lee, Taesup Moon. 4394-4404 [doi]
• LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement LearningYali Du, Lei Han, Meng Fang, Ji Liu, Tianhong Dai, Dacheng Tao. 4405-4416 [doi]
• U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep StagingMathias Perslev, Michael Jensen, Sune Darkner, Poul Jørgen Jennum, Christian Igel. 4417-4428 [doi]
• Massively scalable Sinkhorn distances via the Nyström methodJason Altschuler, Francis Bach, Alessandro Rudi, Jonathan Niles-Weed. 4429-4439 [doi]
• Double Quantization for Communication-Efficient Distributed OptimizationYue Yu, Jiaxiang Wu, Longbo Huang. 4440-4451 [doi]
• Globally optimal score-based learning of directed acyclic graphs in high-dimensionsBryon Aragam, Arash A. Amini, Qing Zhou. 4452-4464 [doi]
• Multi-relational Poincaré Graph EmbeddingsIvana Balazevic, Carl Allen, Timothy M. Hospedales. 4465-4475 [doi]
• No-Press Diplomacy: Modeling Multi-Agent GameplayPhilip Paquette, Yuchen Lu, Steven Bocco, Max O. Smith, Satya Ortiz-Gagne, Jonathan K. Kummerfeld, Joelle Pineau, Satinder Singh, Aaron C. Courville. 4476-4487 [doi]
• State Aggregation Learning from Markov Transition DataYaqi Duan, Zheng Tracy Ke, Mengdi Wang. 4488-4497 [doi]
• Disentangling Influence: Using disentangled representations to audit model predictionsCharles T. Marx, Richard L. Phillips, Sorelle A. Friedler, Carlos Scheidegger, Suresh Venkatasubramanian. 4498-4508 [doi]
• Successor Uncertainties: Exploration and Uncertainty in Temporal Difference LearningDavid Janz, Jiri Hron, Przemyslaw Mazur, Katja Hofmann, José Miguel Hernández-Lobato, Sebastian Tschiatschek. 4509-4518 [doi]
• Partially Encrypted Deep Learning using Functional EncryptionTheo Ryffel, David Pointcheval, Francis Bach, Edouard Dufour Sans, Romain Gay. 4519-4530 [doi]
• Decentralized Cooperative Stochastic BanditsDavid Martínez-Rubio, Varun Kanade, Patrick Rebeschini. 4531-4542 [doi]
• Statistical bounds for entropic optimal transport: sample complexity and the central limit theoremGonzalo Mena, Jonathan Niles-Weed. 4543-4553 [doi]
• Efficient Deep Approximation of GMMsShirin Jalali, Carl J. Nuzman, Iraj Saniee. 4554-4562 [doi]
• Learning low-dimensional state embeddings and metastable clusters from time series dataYifan Sun, Yaqi Duan, Hao Gong, Mengdi Wang. 4563-4572 [doi]
• Exploiting Local and Global Structure for Point Cloud Semantic Segmentation with Contextual Point RepresentationsXu Wang, Jingming He, Lin Ma. 4573-4583 [doi]
• Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processesCreighton Heaukulani, Mark van der Wilk. 4584-4594 [doi]
• Kernel Instrumental Variable RegressionRahul Singh, Maneesh Sahani, Arthur Gretton. 4595-4607 [doi]
• Symmetry-Based Disentangled Representation Learning requires Interaction with EnvironmentsHugo Caselles-Dupré, Michaël Garcia Ortiz, David Filliat. 4608-4617 [doi]
• Fast Efficient Hyperparameter Tuning for Policy Gradient MethodsSupratik Paul, Vitaly Kurin, Shimon Whiteson. 4618-4628 [doi]
• Offline Contextual Bayesian OptimizationIan Char, Youngseog Chung, Willie Neiswanger, Kirthevasan Kandasamy, Oak Nelson, Mark Boyer, Egemen Kolemen. 4629-4640 [doi]
• Making the Cut: A Bandit-based Approach to Tiered InterviewingCandice Schumann, Zhi Lang, Jeffrey S. Foster, John P. Dickerson. 4641-4651 [doi]
• Unsupervised Scalable Representation Learning for Multivariate Time SeriesJean-Yves Franceschi, Aymeric Dieuleveut, Martin Jaggi. 4652-4663 [doi]
• A state-space model for inferring effective connectivity of latent neural dynamics from simultaneous EEG/fMRITao Tu, John Paisley, Stefan Haufe, Paul Sajda. 4664-4673 [doi]
• End to end learning and optimization on graphsBryan Wilder, Eric Ewing, Bistra Dilkina, Milind Tambe. 4674-4685 [doi]
• Game Design for Eliciting Distinguishable BehaviorFan Yang, Liu Leqi, Yifan Wu, Zachary Chase Lipton, Pradeep Ravikumar, Tom M. Mitchell, William W. Cohen. 4686-4695 [doi]
• When does label smoothing help?Rafael Müller, Simon Kornblith, Geoffrey E. Hinton. 4696-4705 [doi]
• Finite-Time Performance Bounds and Adaptive Learning Rate Selection for Two Time-Scale Reinforcement LearningHarsh Gupta, R. Srikant 0001, Lei Ying. 4706-4715 [doi]
• Rethinking Deep Neural Network Ownership Verification: Embedding Passports to Defeat Ambiguity AttacksLixin Fan, KamWoh Ng, Chee Seng Chan. 4716-4725 [doi]
• Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational InferenceCole L. Hurwitz, Kai Xu, Akash Srivastava, Alessio Paolo Buccino, Matthias Hennig. 4726-4738 [doi]
• Optimal Sketching for Kronecker Product Regression and Low Rank ApproximationHuaian Diao, Rajesh Jayaram, Zhao Song, Wen Sun, David P. Woodruff. 4739-4750 [doi]
• Distribution-Independent PAC Learning of Halfspaces with Massart NoiseIlias Diakonikolas, Themis Gouleakis, Christos Tzamos. 4751-4762 [doi]
• The Convergence Rate of Neural Networks for Learned Functions of Different FrequenciesRonen Basri, David W. Jacobs, Yoni Kasten, Shira Kritchman. 4763-4772 [doi]
• Adaptive Auxiliary Task Weighting for Reinforcement LearningXingyu Lin, Harjatin Singh Baweja, George Kantor, David Held. 4773-4784 [doi]
• Blocking BanditsSoumya Basu, Rajat Sen, Sujay Sanghavi, Sanjay Shakkottai. 4785-4794 [doi]
• Global Convergence of Least Squares EM for Demixing Two Log-Concave DensitiesWei Qian, Yuqian Zhang, Yudong Chen. 4795-4803 [doi]
• Prior-Free Dynamic Auctions with Low Regret BuyersYuan Deng, Jon Schneider, Balasubramanian Sivan. 4804-4814 [doi]
• On Single Source Robustness in Deep Fusion ModelsTaewan Kim, Joydeep Ghosh. 4815-4826 [doi]
• Policy Evaluation with Latent Confounders via Optimal BalanceAndrew Bennett, Nathan Kallus. 4827-4837 [doi]
• Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series ForecastingRajat Sen, Hsiang-Fu Yu, Inderjit S. Dhillon. 4838-4847 [doi]
• Adaptive Cross-Modal Few-shot LearningChen Xing, Negar Rostamzadeh, Boris N. Oreshkin, Pedro O. Pinheiro. 4848-4858 [doi]
• Spectral Modification of Graphs for Improved Spectral ClusteringIoannis Koutis, Huong Le. 4859-4868 [doi]
• Hyperbolic Graph Convolutional Neural NetworksInes Chami, Zhitao Ying, Christopher Ré, Jure Leskovec. 4869-4880 [doi]
• Cost Effective Active SearchShali Jiang, Roman Garnett, Benjamin Moseley. 4881-4890 [doi]
• Exploration Bonus for Regret Minimization in Discrete and Continuous Average Reward MDPsJian Qian, Ronan Fruit, Matteo Pirotta, Alessandro Lazaric. 4891-4900 [doi]
• Hybrid 8-bit Floating Point (HFP8) Training and Inference for Deep Neural NetworksXiao Sun, Jungwook Choi, Chia-Yu Chen, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Xiaodong Cui, Wei Zhang, Kailash Gopalakrishnan. 4901-4910 [doi]
• Tight Certificates of Adversarial Robustness for Randomly Smoothed ClassifiersGuang-He Lee, Yang Yuan, Shiyu Chang, Tommi S. Jaakkola. 4911-4922 [doi]
• Poisson-Minibatching for Gibbs Sampling with Convergence Rate GuaranteesRuqi Zhang, Christopher De Sa. 4923-4932 [doi]
• One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizersAri S. Morcos, Haonan Yu, Michela Paganini, Yuandong Tian. 4933-4943 [doi]
• Breaking the Glass Ceiling for Embedding-Based Classifiers for Large Output SpacesChuan Guo, Ali Mousavi, Xiang Wu, Daniel Niels Holtmann-Rice, Satyen Kale, Sashank J. Reddi, Sanjiv Kumar. 4944-4954 [doi]
• Fair Algorithms for ClusteringSuman Kalyan Bera, Deeparnab Chakrabarty, Nicolas Flores, Maryam Negahbani. 4955-4966 [doi]
• Learning Mean-Field GamesXin Guo, Anran Hu, Renyuan Xu, Junzi Zhang. 4967-4977 [doi]
• SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained MicrocontrollersIgor Fedorov, Ryan P. Adams, Matthew Mattina, Paul N. Whatmough. 4978-4990 [doi]
• Deep imitation learning for molecular inverse problemsEric Jonas. 4991-5001 [doi]
• Visual Concept-Metaconcept LearningChi Han, Jiayuan Mao, Chuang Gan, Josh Tenenbaum, Jiajun Wu 0001. 5002-5013 [doi]
• Few-shot Video-to-Video SynthesisTing-chun Wang, Ming-Yu Liu 0001, Andrew Tao, Guilin Liu, Bryan Catanzaro, Jan Kautz. 5014-5025 [doi]
• Neural Similarity LearningWeiyang Liu, Zhen Liu, James M. Rehg, Le Song. 5026-5037 [doi]
• Ordered MemoryYikang Shen, Shawn Tan, Seyed Arian Hosseini, Zhouhan Lin, Alessandro Sordoni, Aaron C. Courville. 5038-5049 [doi]
• MixMatch: A Holistic Approach to Semi-Supervised LearningDavid Berthelot, Nicholas Carlini, Ian J. Goodfellow, Nicolas Papernot, Avital Oliver, Colin Raffel. 5050-5060 [doi]
• Multivariate Triangular Quantile Maps for Novelty DetectionJingjing Wang, Sun Sun, Yaoliang Yu. 5061-5072 [doi]
• Fast Parallel Algorithms for Statistical Subset Selection ProblemsSharon Qian, Yaron Singer. 5073-5082 [doi]
• PHYRE: A New Benchmark for Physical ReasoningAnton Bakhtin, Laurens van der Maaten, Justin Johnson 0001, Laura Gustafson, Ross B. Girshick. 5083-5094 [doi]
• On the number of variables to use in principal component regressionJi Xu, Daniel J. Hsu. 5095-5104 [doi]
• Factor Group-Sparse Regularization for Efficient Low-Rank Matrix RecoveryJicong Fan, Lijun Ding, Yudong Chen 0001, Madeleine Udell. 5105-5115 [doi]
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• Data-driven Estimation of Sinusoid FrequenciesGautier Izacard, Sreyas Mohan, Carlos Fernandez-Granda. 5128-5138 [doi]
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• Learning to Predict Without Looking Ahead: World Models Without Forward PredictionC. Daniel Freeman, David Ha, Luke Metz. 5380-5391 [doi]
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• Characterizing Bias in Classifiers using Generative ModelsDaniel J. McDuff, Shuang Ma, Yale Song, Ashish Kapoor. 5404-5415 [doi]
• Optimal Stochastic and Online Learning with Individual IteratesYunwen Lei, Peng Yang 0008, Ke Tang, Ding-Xuan Zhou. 5416-5426 [doi]
• Policy Learning for Fairness in RankingAshudeep Singh, Thorsten Joachims. 5427-5437 [doi]
• Off-Policy Evaluation via Off-Policy ClassificationAlexander Irpan, Kanishka Rao, Konstantinos Bousmalis, Chris Harris, Julian Ibarz, Sergey Levine. 5438-5449 [doi]
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• Markov Random Fields for Collaborative FilteringHarald Steck. 5474-5485 [doi]
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• Exploring Unexplored Tensor Network Decompositions for Convolutional Neural NetworksKohei Hayashi, Taiki Yamaguchi, Yohei Sugawara, Shin-ichi Maeda. 5553-5563 [doi]
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• Adaptive Influence Maximization with Myopic FeedbackBinghui Peng, Wei Chen. 5575-5584 [doi]
• Focused Quantization for Sparse CNNsYiren Zhao, Xitong Gao, Daniel Bates, Robert Mullins, Cheng-Zhong Xu 0001. 5585-5594 [doi]
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• Optimal Best Markovian Arm Identification with Fixed ConfidenceVrettos Moulos. 5606-5615 [doi]
• Limiting Extrapolation in Linear Approximate Value IterationAndrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill. 5616-5625 [doi]
• Almost Horizon-Free Structure-Aware Best Policy Identification with a Generative ModelAndrea Zanette, Mykel J. Kochenderfer, Emma Brunskill. 5626-5635 [doi]
• Invertible Convolutional FlowMahdi Karami, Dale Schuurmans, Jascha Sohl-Dickstein, Laurent Dinh, Daniel Duckworth. 5636-5646 [doi]
• A Latent Variational Framework for Stochastic OptimizationPhilippe Casgrain. 5647-5657 [doi]
• Topology-Preserving Deep Image SegmentationXiaoling Hu, Fuxin Li, Dimitris Samaras, Chao Chen. 5658-5669 [doi]
• Connective Cognition Network for Directional Visual Commonsense ReasoningAming Wu, Linchao Zhu, Yahong Han, Yi Yang. 5670-5680 [doi]
• Online Markov Decoding: Lower Bounds and Near-Optimal Approximation AlgorithmsVikas K. Garg, Tamar Pichkhadze. 5681-5691 [doi]
• A Meta-MDP Approach to Exploration for Lifelong Reinforcement LearningFrancisco M. Garcia, Philip S. Thomas. 5692-5701 [doi]
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• Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph KernelsSimon S. Du, Kangcheng Hou, Ruslan Salakhutdinov, Barnabás Póczos, Ruosong Wang, Keyulu Xu. 5724-5734 [doi]
• In-Place Zero-Space Memory Protection for CNNHui Guan, Lin Ning, Zhen Lin, Xipeng Shen, Huiyang Zhou, Seung-Hwan Lim. 5735-5744 [doi]
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• Learning GANs and Ensembles Using DiscrepancyBen Adlam, Corinna Cortes, Mehryar Mohri, Ningshan Zhang. 5788-5799 [doi]
• Co-Generation with GANs using AIS based HMCTiantian Fang, Alexander G. Schwing. 5800-5811 [doi]
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• A Regularized Approach to Sparse Optimal Policy in Reinforcement LearningWenhao Yang, Xiang Li, Zhihua Zhang. 5938-5948 [doi]
• Scalable inference of topic evolution via models for latent geometric structuresMikhail Yurochkin, Zhiwei Fan, Aritra Guha, Paraschos Koutris, XuanLong Nguyen. 5949-5959 [doi]
• Effective End-to-end Unsupervised Outlier Detection via Inlier Priority of Discriminative NetworkSiqi Wang, Yijie Zeng, Xinwang Liu, En Zhu, Jianping Yin, Chuanfu Xu, Marius Kloft. 5960-5973 [doi]
• Deep Active Learning with a Neural Architecture SearchYonatan Geifman, Ran El-Yaniv. 5974-5984 [doi]
• Efficiently escaping saddle points on manifoldsChris Criscitiello, Nicolas Boumal. 5985-5995 [doi]
• AutoAssist: A Framework to Accelerate Training of Deep Neural NetworksJiong Zhang, Hsiang-Fu Yu, Inderjit S. Dhillon. 5996-6006 [doi]
• DFNets: Spectral CNNs for Graphs with Feedback-Looped FiltersAsiri Wijesinghe, Qing Wang. 6007-6018 [doi]
• Learning Dynamics of Attention: Human Prior for Interpretable Machine ReasoningWonjae Kim, Yoonho Lee. 6019-6030 [doi]
• Comparing Unsupervised Word Translation Methods Step by StepMareike Hartmann, Yova Kementchedjhieva, Anders Søgaard. 6031-6041 [doi]
• Learning from Bad Data via GenerationTianyu Guo, Chang Xu 0002, Boxin Shi, Chao Xu 0006, Dacheng Tao. 6042-6053 [doi]
• Constrained deep neural network architecture search for IoT devices accounting for hardware calibrationFlorian Scheidegger, Luca Benini, Costas Bekas, A. Cristiano I. Malossi. 6054-6064 [doi]
• Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier DetectionYihe Dong, Samuel B. Hopkins, Jerry Li 0001. 6065-6075 [doi]
• Iterative Least Trimmed Squares for Mixed Linear RegressionYanyao Shen, Sujay Sanghavi. 6076-6086 [doi]
• Dynamic Ensemble Modeling Approach to Nonstationary Neural Decoding in Brain-Computer InterfacesYu Qi, Bin Liu, Yueming Wang, Gang Pan 0001. 6087-6096 [doi]
• Divergence-Augmented Policy OptimizationQing Wang, Yingru Li, Jiechao Xiong, Tong Zhang. 6097-6108 [doi]
• Intrinsic dimension of data representations in deep neural networksAlessio Ansuini, Alessandro Laio, Jakob H. Macke, Davide Zoccolan. 6109-6119 [doi]
• Towards a Zero-One Law for Column Subset SelectionZhao Song, David P. Woodruff, Peilin Zhong. 6120-6131 [doi]
• Compositional De-Attention NetworksYi Tay, Anh Tuan Luu, Aston Zhang, Shuohang Wang, Siu Cheung Hui. 6132-6142 [doi]
• Dual Adversarial Semantics-Consistent Network for Generalized Zero-Shot LearningJian Ni, Shanghang Zhang, Haiyong Xie 0001. 6143-6154 [doi]
• Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two LayersZeyuan Allen Zhu, Yuanzhi Li, Yingyu Liang. 6155-6166 [doi]
• Mining GOLD Samples for Conditional GANsSangwoo Mo, Chiheon Kim, Sungwoong Kim, Minsu Cho, Jinwoo Shin. 6167-6178 [doi]
• Deep Model Transferability from Attribution MapsJie Song, Yixin Chen, Xinchao Wang, Chengchao Shen, Mingli Song. 6179-6189 [doi]
• Fully Parameterized Quantile Function for Distributional Reinforcement LearningDerek Yang, Li Zhao, Zichuan Lin, Tao Qin, Jiang Bian 0002, Tie-Yan Liu. 6190-6199 [doi]
• Direct Optimization through arg max for Discrete Variational Auto-EncoderGuy Lorberbom, Tommi S. Jaakkola, Andreea Gane, Tamir Hazan. 6200-6211 [doi]
• Distributional Reward Decomposition for Reinforcement LearningZichuan Lin, Li Zhao, Derek Yang, Tao Qin, Tie-Yan Liu, Guangwen Yang. 6212-6221 [doi]
• L_DMI: A Novel Information-theoretic Loss Function for Training Deep Nets Robust to Label NoiseYilun Xu, Peng Cao, Yuqing Kong, Yizhou Wang. 6222-6233 [doi]
• Convergence Guarantees for Adaptive Bayesian Quadrature MethodsMotonobu Kanagawa, Philipp Hennig. 6234-6245 [doi]
• Progressive Augmentation of GANsDan Zhang, Anna Khoreva. 6246-6256 [doi]
• UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained OptimizationAli Kavis, Kfir Y. Levy, Francis Bach, Volkan Cevher. 6257-6266 [doi]
• Meta-Surrogate Benchmarking for Hyperparameter OptimizationAaron Klein, Zhenwen Dai, Frank Hutter, Neil D. Lawrence, Javier Gonzalez. 6267-6277 [doi]
• Learning to Perform Local Rewriting for Combinatorial OptimizationXinyun Chen, Yuandong Tian. 6278-6289 [doi]
• Anti-efficient encoding in emergent communicationRahma Chaabouni, Eugene Kharitonov, Emmanuel Dupoux, Marco Baroni. 6290-6300 [doi]
• Singleshot : a scalable Tucker tensor decompositionAbraham Traore, Maxime Berar, Alain Rakotomamonjy. 6301-6312 [doi]
• Neural Machine Translation with Soft PrototypeYiren Wang, Yingce Xia, Fei Tian, Fei Gao, Tao Qin, ChengXiang Zhai, Tie-Yan Liu. 6313-6322 [doi]
• Reliable training and estimation of variance networksNicki Skafte Detlefsen, Martin Jørgensen, Søren Hauberg. 6323-6333 [doi]
• Copula Multi-label LearningWeiwei Liu. 6334-6343 [doi]
• Bayesian Learning of Sum-Product NetworksMartin Trapp, Robert Peharz, Hong Ge, Franz Pernkopf, Zoubin Ghahramani. 6344-6355 [doi]
• Bayesian Batch Active Learning as Sparse Subset ApproximationRobert Pinsler, Jonathan Gordon 0003, Eric T. Nalisnick, José Miguel Hernández-Lobato. 6356-6367 [doi]
• Optimal Sparsity-Sensitive Bounds for Distributed Mean EstimationZengfeng Huang, Ziyue Huang, Yilei Wang, Ke Yi 0001. 6368-6378 [doi]
• Global Sparse Momentum SGD for Pruning Very Deep Neural NetworksXiaohan Ding,