Table of Contents

• Efficient Algorithms for Non-convex Isotonic Regression through Submodular OptimizationFrancis Bach. 1-10 [doi]
• Structure-Aware Convolutional Neural NetworksJianlong Chang, Jie Gu, Lingfeng Wang, Gaofeng Meng, Shiming Xiang, Chunhong Pan. 11-20 [doi]
• Kalman Normalization: Normalizing Internal Representations Across Network LayersGuangrun Wang, Jiefeng Peng, Ping Luo 0002, Xinjiang Wang, Liang Lin. 21-31 [doi]
• HOGWILD!-Gibbs can be PanAccurateConstantinos Daskalakis, Nishanth Dikkala, Siddhartha Jayanti. 32-41 [doi]
• Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural LanguageSeonghyeon Nam, Yunji Kim, Seon Joo Kim. 42-51 [doi]
• IntroVAE: Introspective Variational Autoencoders for Photographic Image SynthesisHuaibo Huang, Zhihang Li, Ran He, Zhenan Sun, Tieniu Tan. 52-63 [doi]
• Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with \beta-DivergencesJeremias Knoblauch, Jack Jewson, Theodoros Damoulas. 64-75 [doi]
• Adapted Deep Embeddings: A Synthesis of Methods for k-Shot Inductive Transfer LearningTyler R. Scott, Karl Ridgeway, Michael C. Mozer. 76-85 [doi]
• Generalized Inverse Optimization through Online LearningChaosheng Dong, Yiran Chen, Bo Zeng. 86-95 [doi]
• An Off-policy Policy Gradient Theorem Using Emphatic WeightingsEhsan Imani, Eric Graves, Martha White. 96-106 [doi]
• Supervised autoencoders: Improving generalization performance with unsupervised regularizersLei Le, Andrew Patterson, Martha White. 107-117 [doi]
• Visual Object Networks: Image Generation with Disentangled 3D RepresentationsJun-Yan Zhu, Zhoutong Zhang, Chengkai Zhang, Jiajun Wu 0001, Antonio Torralba 0001, Josh Tenenbaum, Bill Freeman. 118-129 [doi]
• Understanding Weight Normalized Deep Neural Networks with Rectified Linear UnitsYixi Xu, Xiao Wang. 130-139 [doi]
• Learning Pipelines with Limited Data and Domain Knowledge: A Study in Parsing Physics ProblemsMrinmaya Sachan, Kumar Avinava Dubey, Tom M. Mitchell, Dan Roth, Eric P. Xing. 140-151 [doi]
• Learning long-range spatial dependencies with horizontal gated recurrent unitsDrew Linsley, Junkyung Kim, Vijay Veerabadran, Charles Windolf, Thomas Serre. 152-164 [doi]
• Joint Sub-bands Learning with Clique Structures for Wavelet Domain Super-ResolutionZhisheng Zhong, Tiancheng Shen, Yibo Yang, Zhouchen Lin, Chao Zhang. 165-175 [doi]
• Fast Similarity Search via Optimal Sparse LiftingWenye Li, Jingwei Mao, Yin Zhang, Shuguang Cui. 176-184 [doi]
• Learning Deep Disentangled Embeddings With the F-Statistic LossKarl Ridgeway, Michael C. Mozer. 185-194 [doi]
• Geometrically Coupled Monte Carlo SamplingMark Rowland, Krzysztof Choromanski, François Chalus, Aldo Pacchiano, Tamás Sarlós, Richard E. Turner, Adrian Weller. 195-205 [doi]
• Cooperative Holistic Scene Understanding: Unifying 3D Object, Layout, and Camera Pose EstimationSiyuan Huang, Siyuan Qi, Yinxue Xiao, Yixin Zhu, Ying Nian Wu, Song Chun Zhu. 206-217 [doi]
• An Efficient Pruning Algorithm for Robust Isotonic RegressionCong Han Lim. 218-227 [doi]
• PAC-learning in the presence of adversariesDaniel Cullina, Arjun Nitin Bhagoji, Prateek Mittal. 228-239 [doi]
• Sparse DNNs with Improved Adversarial RobustnessYiwen Guo, Chao Zhang, Changshui Zhang, Yurong Chen. 240-249 [doi]
• Snap ML: A Hierarchical Framework for Machine LearningCelestine Dünner, Thomas P. Parnell, Dimitrios Sarigiannis, Nikolas Ioannou, Andreea Anghel, Gummadi Ravi, Madhusudanan Kandasamy, Haralampos Pozidis. 250-260 [doi]
• See and Think: Disentangling Semantic Scene CompletionShice Liu, Yu Hu, Yiming Zeng, Qiankun Tang, Beibei Jin, Yinhe Han, Xiaowei Li. 261-272 [doi]
• Chain of Reasoning for Visual Question AnsweringChenfei Wu, Jinlai Liu, Xiaojie Wang, Xuan Dong. 273-283 [doi]
• Sigsoftmax: Reanalysis of the Softmax BottleneckSekitoshi Kanai, Yasuhiro Fujiwara, Yuki Yamanaka, Shuichi Adachi. 284-294 [doi]
• Deep Non-Blind Deconvolution via Generalized Low-Rank ApproximationWenqi Ren, Jiawei Zhang, Lin Ma 0002, Jinshan Pan, Xiaochun Cao, Wangmeng Zuo, Wei Liu, Ming-Hsuan Yang 0001. 295-305 [doi]
• Bayesian Pose Graph Optimization via Bingham Distributions and Tempered Geodesic MCMCTolga Birdal, Umut Simsekli, Mustafa Onur Eken, Slobodan Ilic. 306-317 [doi]
• MetaAnchor: Learning to Detect Objects with Customized AnchorsTong Yang, Xiangyu Zhang, Zeming Li, Wenqiang Zhang, Jian Sun. 318-328 [doi]
• Image Inpainting via Generative Multi-column Convolutional Neural NetworksYi Wang, Xin Tao, Xiaojuan Qi, Xiaoyong Shen, Jiaya Jia. 329-338 [doi]
• On Misinformation Containment in Online Social NetworksGuangmo Amo Tong, Ding-Zhu Du, Weili Wu. 339-349 [doi]
• A^2-Nets: Double Attention NetworksYunpeng Chen, Yannis Kalantidis, Jianshu Li, Shuicheng Yan, Jiashi Feng. 350-359 [doi]
• Self-Supervised Generation of Spatial Audio for 360° VideoPedro Morgado, Nuno Vasconcelos, Timothy R. Langlois, Oliver Wang. 360-370 [doi]
• How Many Samples are Needed to Estimate a Convolutional Neural Network?Simon S. Du, Yining Wang, Xiyu Zhai, Sivaraman Balakrishnan, Ruslan R. Salakhutdinov, Aarti Singh. 371-381 [doi]
• Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically BalancedSimon S. Du, Wei Hu, Jason D. Lee. 382-393 [doi]
• Optimization for Approximate SubmodularityYaron Singer, Avinatan Hassidim. 394-405 [doi]
• (Probably) Concave Graph MatchingHaggai Maron, Yaron Lipman. 406-416 [doi]
• Deep Defense: Training DNNs with Improved Adversarial RobustnessZiang Yan, Yiwen Guo, Changshui Zhang. 417-426 [doi]
• Rest-Katyusha: Exploiting the Solution's Structure via Scheduled Restart SchemesJunqi Tang, Mohammad Golbabaee, Francis Bach, Mike E. Davies. 427-438 [doi]
• Implicit Reparameterization GradientsMikhail Figurnov, Shakir Mohamed, Andriy Mnih. 439-450 [doi]
• Training DNNs with Hybrid Block Floating PointMario Drumond, Tao Lin, Martin Jaggi, Babak Falsafi. 451-461 [doi]
• A Model for Learned Bloom Filters and Optimizing by SandwichingMichael Mitzenmacher. 462-471 [doi]
• Soft-Gated Warping-GAN for Pose-Guided Person Image SynthesisHaoye Dong, Xiaodan Liang, Ke Gong, Hanjiang Lai, Jia Zhu, Jian Yin. 472-482 [doi]
• Deep Functional Dictionaries: Learning Consistent Semantic Structures on 3D Models from FunctionsMinhyuk Sung, Hao Su, Ronald Yu, Leonidas J. Guibas. 483-493 [doi]
• Nonlocal Neural Networks, Nonlocal Diffusion and Nonlocal ModelingYunzhe Tao, Qi Sun, Qiang Du, Wei Liu. 494-504 [doi]
• Are ResNets Provably Better than Linear Predictors?Ohad Shamir. 505-514 [doi]
• Learning to Decompose and Disentangle Representations for Video PredictionJun-Ting Hsieh, Bingbin Liu, De-An Huang, Fei-Fei Li, Juan Carlos Niebles. 515-524 [doi]
• Multi-Task Learning as Multi-Objective OptimizationOzan Sener, Vladlen Koltun. 525-536 [doi]
• Combinatorial Optimization with Graph Convolutional Networks and Guided Tree SearchZhuwen Li, Qifeng Chen, Vladlen Koltun. 537-546 [doi]
• Self-Erasing Network for Integral Object AttentionQibin Hou, Peng-Tao Jiang, Yunchao Wei, Ming-Ming Cheng. 547-557 [doi]
• LinkNet: Relational Embedding for Scene GraphSanghyun Woo, Dahun Kim, Donghyeon Cho, In-So Kweon. 558-568 [doi]
• How to Start Training: The Effect of Initialization and ArchitectureBoris Hanin, David Rolnick. 569-579 [doi]
• Which Neural Net Architectures Give Rise to Exploding and Vanishing Gradients?Boris Hanin. 580-589 [doi]
• Explanations based on the Missing: Towards Contrastive Explanations with Pertinent NegativesAmit Dhurandhar, Pin-Yu Chen, Ronny Luss, Chun Chen Tu, Pai-Shun Ting, Karthikeyan Shanmugam, Payel Das. 590-601 [doi]
• HitNet: Hybrid Ternary Recurrent Neural NetworkPeiqi Wang, Xinfeng Xie, Lei Deng, Guoqi Li, Dongsheng Wang, Yuan Xie. 602-612 [doi]
• A Unified Framework for Extensive-Form Game Abstraction with BoundsChristian Kroer, Tuomas Sandholm. 613-624 [doi]
• Removing the Feature Correlation Effect of Multiplicative NoiseZijun Zhang, Yining Zhang, Zongpeng Li. 625-634 [doi]
• Maximum-Entropy Fine Grained ClassificationAbhimanyu Dubey, Otkrist Gupta, Ramesh Raskar, Nikhil Naik. 635-645 [doi]
• On Learning Markov ChainsYi Hao, Alon Orlitsky, Venkatadheeraj Pichapati. 646-655 [doi]
• A Neural Compositional Paradigm for Image CaptioningBo Dai, Sanja Fidler, Dahua Lin. 656-666 [doi]
• Quantifying Learning Guarantees for Convex but Inconsistent SurrogatesKirill Struminsky, Simon Lacoste-Julien, Anton Osokin. 667-675 [doi]
• Dialog-based Interactive Image RetrievalXiaoxiao Guo, Hui Wu, Yu Cheng, Steven Rennie, Gerald Tesauro, Rogério Schmidt Feris. 676-686 [doi]
• SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential EstimatorCong Fang, Chris Junchi Li, Zhouchen Lin, Tong Zhang. 687-697 [doi]
• Are GANs Created Equal? A Large-Scale StudyMario Lucic, Karol Kurach, Marcin Michalski, Sylvain Gelly, Olivier Bousquet. 698-707 [doi]
• Learning Disentangled Joint Continuous and Discrete RepresentationsEmilien Dupont. 708-718 [doi]
• TADAM: Task dependent adaptive metric for improved few-shot learningBoris N. Oreshkin, Pau Rodríguez López, Alexandre Lacoste. 719-729 [doi]
• Do Less, Get More: Streaming Submodular Maximization with SubsamplingMoran Feldman, Amin Karbasi, Ehsan Kazemi 0001. 730-740 [doi]
• Sparse Covariance Modeling in High Dimensions with Gaussian ProcessesRui Li 0002, Kishan KC, Feng Cui, Justin Domke, Anne R. Haake. 741-750 [doi]
• Deep Neural Nets with Interpolating Function as Output ActivationBao Wang, Xiyang Luo, Zhen Li, Wei Zhu, Zuoqiang Shi, Stanley Osher. 751-761 [doi]
• FishNet: A Versatile Backbone for Image, Region, and Pixel Level PredictionShuyang Sun, Jiangmiao Pang, Jianping Shi, Shuai Yi, Wanli Ouyang. 762-772 [doi]
• Visual Memory for Robust Path FollowingAshish Kumar, Saurabh Gupta, David F. Fouhey, Sergey Levine, Jitendra Malik. 773-782 [doi]
• KDGAN: Knowledge Distillation with Generative Adversarial NetworksXiaojie Wang, Rui Zhang, Yu Sun 0021, Jianzhong Qi. 783-794 [doi]
• Long short-term memory and Learning-to-learn in networks of spiking neuronsGuillaume Bellec, Darjan Salaj, Anand Subramoney, Robert A. Legenstein, Wolfgang Maass 0001. 795-805 [doi]
• Greedy Hash: Towards Fast Optimization for Accurate Hash Coding in CNNShupeng Su, Chao Zhang, Kai Han, YongHong Tian. 806-815 [doi]
• Informative Features for Model ComparisonWittawat Jitkrittum, Heishiro Kanagawa, Patsorn Sangkloy, James Hays, Bernhard Schölkopf, Arthur Gretton. 816-827 [doi]
• PointCNN: Convolution On X-Transformed PointsYangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, Baoquan Chen. 828-838 [doi]
• Connectionist Temporal Classification with Maximum Entropy RegularizationHu Liu, Sheng Jin, Changshui Zhang. 839-849 [doi]
• Large Margin Deep Networks for ClassificationGamaleldin F. Elsayed, Dilip Krishnan, Hossein Mobahi, Kevin Regan, Samy Bengio. 850-860 [doi]
• Generalizing Graph Matching beyond Quadratic Assignment ModelTianshu Yu, Junchi Yan, Yilin Wang, Wei Liu, Baoxin Li. 861-871 [doi]
• Solving Large Sequential Games with the Excessive Gap TechniqueChristian Kroer, Gabriele Farina, Tuomas Sandholm. 872-882 [doi]
• Discrimination-aware Channel Pruning for Deep Neural NetworksZhuangwei Zhuang, Mingkui Tan, Bohan Zhuang, Jing Liu, Yong Guo, Qingyao Wu, JunZhou Huang, Jin-Hui Zhu. 883-894 [doi]
• On the Dimensionality of Word EmbeddingZi Yin, Yuanyuan Shen. 895-906 [doi]
• Reinforced Continual LearningJu Xu, Zhanxing Zhu. 907-916 [doi]
• Uncertainty-Aware Attention for Reliable Interpretation and PredictionJay Heo, Haebeom Lee, Saehoon Kim, Juho Lee, Kwang joon Kim, Eunho Yang, Sung Ju Hwang. 917-926 [doi]
• DropMax: Adaptive Variational SoftmaxHaebeom Lee, Juho Lee, Saehoon Kim, Eunho Yang, Sung Ju Hwang. 927-937 [doi]
• Posterior Concentration for Sparse Deep LearningVeronika Rocková, Nicholas Polson. 938-949 [doi]
• A flexible model for training action localization with varying levels of supervisionGuilhem Chéron, Jean-Baptiste Alayrac, Ivan Laptev, Cordelia Schmid. 950-961 [doi]
• A Deep Bayesian Policy Reuse Approach Against Non-Stationary AgentsYan Zheng, Zhaopeng Meng, Jianye Hao, Zongzhang Zhang, Tianpei Yang, Changjie Fan. 962-972 [doi]
• Empirical Risk Minimization in Non-interactive Local Differential Privacy RevisitedDi Wang 0015, Marco Gaboardi, Jinhui Xu 0001. 973-982 [doi]
• Low-shot Learning via Covariance-Preserving Adversarial Augmentation NetworksHang Gao, Zheng Shou, Alireza Zareian, Hanwang Zhang, Shih-Fu Chang. 983-993 [doi]
• Learning semantic similarity in a continuous spaceMichel Deudon. 994-1005 [doi]
• MetaReg: Towards Domain Generalization using Meta-RegularizationYogesh Balaji, Swami Sankaranarayanan, Rama Chellappa. 1006-1016 [doi]
• Boosted Sparse and Low-Rank Tensor RegressionLifang He 0001, Kun Chen 0002, Wanwan Xu, Jiayu Zhou, Fei Wang. 1017-1026 [doi]
• Domain-Invariant Projection Learning for Zero-Shot RecognitionAn Zhao, Mingyu Ding, Jiechao Guan, Zhiwu Lu, Tao Xiang, Ji-Rong Wen. 1027-1038 [doi]
• Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language UnderstandingKexin Yi, Jiajun Wu 0001, Chuang Gan, Antonio Torralba 0001, Pushmeet Kohli, Josh Tenenbaum. 1039-1050 [doi]
• Frequency-Domain Dynamic Pruning for Convolutional Neural NetworksZhenhua Liu, Jizheng Xu, Xiulian Peng, Ruiqin Xiong. 1051-1061 [doi]
• Quadratic Decomposable Submodular Function MinimizationPan Li, Niao He, Olgica Milenkovic. 1062-1072 [doi]
• A Block Coordinate Ascent Algorithm for Mean-Variance OptimizationTengyang Xie, Bo Liu, Yangyang Xu, Mohammad Ghavamzadeh, Yinlam Chow, Daoming Lyu, Daesub Yoon. 1073-1083 [doi]
• \ell_1-regression with Heavy-tailed DistributionsLijun Zhang, Zhi-Hua Zhou. 1084-1094 [doi]
• Neural Nearest Neighbors NetworksTobias Plötz, Stefan Roth 0001. 1095-1106 [doi]
• Efficient nonmyopic batch active searchShali Jiang, Gustavo Malkomes, Matthew Abbott, Benjamin Moseley, Roman Garnett. 1107-1117 [doi]
• A Game-Theoretic Approach to Recommendation Systems with Strategic Content ProvidersOmer Ben-Porat, Moshe Tennenholtz. 1118-1128 [doi]
• Interactive Structure Learning with Structural Query-by-CommitteeChristopher Tosh, Sanjoy Dasgupta. 1129-1139 [doi]
• Global Geometry of Multichannel Sparse Blind Deconvolution on the SphereYanjun Li, Yoram Bresler. 1140-1151 [doi]
• Video-to-Video SynthesisTing-chun Wang, Ming-Yu Liu 0001, Jun-Yan Zhu, Nikolai Yakovenko, Andrew Tao, Jan Kautz, Bryan Catanzaro. 1152-1164 [doi]
• How To Make the Gradients Small Stochastically: Even Faster Convex and Nonconvex SGDZeyuan Allen Zhu. 1165-1175 [doi]
• Synthesize Policies for Transfer and Adaptation across Tasks and EnvironmentsHexiang Hu, Liyu Chen, Boqing Gong, Fei Sha. 1176-1185 [doi]
• Adversarial vulnerability for any classifierAlhussein Fawzi, Hamza Fawzi, Omar Fawzi. 1186-1195 [doi]
• Evolution-Guided Policy Gradient in Reinforcement LearningShauharda Khadka, Kagan Tumer. 1196-1208 [doi]
• Toddler-Inspired Visual Object LearningSven Bambach, David J. Crandall, Linda B. Smith, Chen Yu. 1209-1218 [doi]
• Alternating optimization of decision trees, with application to learning sparse oblique treesMiguel Á. Carreira-Perpiñán, Pooya Tavallali. 1219-1229 [doi]
• FD-GAN: Pose-guided Feature Distilling GAN for Robust Person Re-identificationYixiao Ge, Zhuowan Li, Haiyu Zhao, Guojun Yin, Shuai Yi, Xiaogang Wang, Hongsheng Li. 1230-1241 [doi]
• New Insight into Hybrid Stochastic Gradient Descent: Beyond With-Replacement Sampling and ConvexityPan Zhou, Xiaotong Yuan, Jiashi Feng. 1242-1251 [doi]
• The Lingering of Gradients: How to Reuse Gradients Over TimeZeyuan Allen Zhu, David Simchi-Levi, Xinshang Wang. 1252-1261 [doi]
• Unsupervised Learning of View-invariant Action RepresentationsJunnan Li, Yongkang Wong, Qi Zhao, Mohan S. Kankanhalli. 1262-1272 [doi]
• Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision MakingHoda Heidari, Claudio Ferrari, Krishna P. Gummadi, Andreas Krause. 1273-1283 [doi]
• Global Gated Mixture of Second-order Pooling for Improving Deep Convolutional Neural NetworksQilong Wang, Zilin Gao, Jiangtao Xie, Wangmeng Zuo, Peihua Li. 1284-1293 [doi]
• Image-to-image translation for cross-domain disentanglementAbel Gonzalez-Garcia, Joost van de Weijer, Yoshua Bengio. 1294-1305 [doi]
• Gradient Sparsification for Communication-Efficient Distributed OptimizationJianqiao Wangni, Jialei Wang, Ji Liu, Tong Zhang. 1306-1316 [doi]
• Revisiting Multi-Task Learning with ROCK: a Deep Residual Auxiliary Block for Visual DetectionTaylor Mordan, Nicolas Thome, Gilles Henaff, Matthieu Cord. 1317-1329 [doi]
• Adaptive Online Learning in Dynamic EnvironmentsLijun Zhang, Shiyin Lu, Zhi-Hua Zhou. 1330-1340 [doi]
• FRAGE: Frequency-Agnostic Word RepresentationChengYue Gong, Di He, Xu Tan, Tao Qin, Liwei Wang 0001, Tie-Yan Liu. 1341-1352 [doi]
• Generative Neural Machine TranslationHarshil Shah, David Barber. 1353-1362 [doi]
• Found Graph Data and Planted Vertex CoversAustin R. Benson, Jon M. Kleinberg. 1363-1374 [doi]
• Joint Active Feature Acquisition and Classification with Variable-Size Set EncodingHajin Shim, Sung Ju Hwang, Eunho Yang. 1375-1385 [doi]
• Regularization Learning Networks: Deep Learning for Tabular DatasetsIra Shavitt, Eran Segal. 1386-1396 [doi]
• Multitask Boosting for Survival Analysis with Competing RisksAlexis Bellot, Mihaela van der Schaar. 1397-1406 [doi]
• Geometry Based Data GenerationOfir Lindenbaum, Jay S. Stanley III, Guy Wolf, Smita Krishnaswamy. 1407-1418 [doi]
• SLAYER: Spike Layer Error Reassignment in TimeSumit Bam Shrestha, Garrick Orchard. 1419-1428 [doi]
• On Oracle-Efficient PAC RL with Rich ObservationsChristoph Dann, Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford 0001, Robert E. Schapire. 1429-1439 [doi]
• Gradient Descent for Spiking Neural NetworksDongsung Huh, Terrence J. Sejnowski. 1440-1450 [doi]
• Generalizing Tree Probability Estimation via Bayesian NetworksCheng Zhang, Frederick A. Matsen IV. 1451-1460 [doi]
• Where Do You Think You're Going?: Inferring Beliefs about Dynamics from BehaviorSiddharth Reddy, Anca D. Dragan, Sergey Levine. 1461-1472 [doi]
• Designing by Training: Acceleration Neural Network for Fast High-Dimensional ConvolutionLongquan Dai, Liang Tang, Yuan Xie 0006, Jinhui Tang. 1473-1482 [doi]
• Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space LearnersYuxin Chen, Adish Singla, Oisin Mac Aodha, Pietro Perona, Yisong Yue. 1483-1493 [doi]
• A loss framework for calibrated anomaly detection1494-1504 [doi]
• PacGAN: The power of two samples in generative adversarial networksZinan Lin, Ashish Khetan, Giulia C. Fanti, Sewoong Oh. 1505-1514 [doi]
• Variational Memory Encoder-DecoderHung Le, Truyen Tran 0001, Thin Nguyen, Svetha Venkatesh. 1515-1525 [doi]
• Stochastic Composite Mirror Descent: Optimal Bounds with High ProbabilitiesYunwen Lei, Ke Tang. 1526-1536 [doi]
• Hybrid Retrieval-Generation Reinforced Agent for Medical Image Report GenerationYuan Li, Xiaodan Liang, Zhiting Hu, Eric P. Xing. 1537-1547 [doi]
• Overcoming Language Priors in Visual Question Answering with Adversarial RegularizationSainandan Ramakrishnan, Aishwarya Agrawal, Stefan Lee. 1548-1558 [doi]
• Hybrid Knowledge Routed Modules for Large-scale Object DetectionChenhan Jiang, Hang Xu, Xiaodan Liang, Liang Lin. 1559-1570 [doi]
• Bilinear Attention NetworksJin-Hwa Kim, Jaehyun Jun, Byoung-Tak Zhang. 1571-1581 [doi]
• Parsimonious Quantile Regression of Financial Asset Tail Dynamics via Sequential LearningXing Yan, Weizhong Zhang, Lin Ma, Wei Liu, Qi Wu. 1582-1592 [doi]
• Multi-Class Learning: From Theory to AlgorithmJian Li, Yong Liu, Rong Yin, Hua Zhang, Lizhong Ding, Weiping Wang. 1593-1602 [doi]
• Multivariate Time Series Imputation with Generative Adversarial NetworksYonghong Luo, Xiangrui Cai, Ying Zhang, Jun Xu, Xiaojie Yuan. 1603-1614 [doi]
• Learning Versatile Filters for Efficient Convolutional Neural NetworksYunhe Wang, Chang Xu, Chunjing Xu, Chao Xu 0006, Dacheng Tao. 1615-1625 [doi]
• Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order OptimizationRobert M. Gower, Filip Hanzely, Peter Richtárik, Sebastian U. Stich. 1626-1636 [doi]
• DifNet: Semantic Segmentation by Diffusion NetworksPeng Jiang, Fanglin Gu, Yunhai Wang, Changhe Tu, Baoquan Chen. 1637-1646 [doi]
• Conditional Adversarial Domain AdaptationMingsheng Long, Zhangjie Cao, Jianmin Wang 0001, Michael I. Jordan. 1647-1657 [doi]
• Neighbourhood Consensus NetworksIgnacio Rocco, Mircea Cimpoi, Relja Arandjelovic, Akihiko Torii, Tomás Pajdla, Josef Sivic. 1658-1669 [doi]
• Relating Leverage Scores and Density using Regularized Christoffel FunctionsEdouard Pauwels, Francis Bach, Jean-Philippe Vert. 1670-1679 [doi]
• Non-Local Recurrent Network for Image RestorationDing Liu, Bihan Wen, Yuchen Fan, Chen Change Loy, Thomas S. Huang. 1680-1689 [doi]
• Bayesian Semi-supervised Learning with Graph Gaussian ProcessesYin Cheng Ng, Nicolò Colombo, Ricardo Silva. 1690-1701 [doi]
• Foreground Clustering for Joint Segmentation and Localization in Videos and ImagesAbhishek Sharma. 1702-1711 [doi]
• Video Prediction via Selective SamplingJingwei Xu, Bingbing Ni, Xiaokang Yang. 1712-1722 [doi]
• Distilled Wasserstein Learning for Word Embedding and Topic ModelingHongteng Xu, Wenlin Wang, Wei Liu, Lawrence Carin. 1723-1732 [doi]
• Learning to Exploit Stability for 3D Scene ParsingYilun Du, Zhijian Liu, Hector Basevi, Ales Leonardis, Bill Freeman, Josh Tenenbaum, Jiajun Wu 0001. 1733-1743 [doi]
• Neural Guided Constraint Logic Programming for Program SynthesisLisa Zhang, Gregory Rosenblatt, Ethan Fetaya, Renjie Liao, William E. Byrd, Matthew Might, Raquel Urtasun, Richard S. Zemel. 1744-1753 [doi]
• Genetic-Gated Networks for Deep Reinforcement LearningSimyung Chang, John Yang, Jaeseok Choi, Nojun Kwak. 1754-1763 [doi]
• Fighting Boredom in Recommender Systems with Linear Reinforcement LearningRomain Warlop, Alessandro Lazaric, Jérémie Mary. 1764-1773 [doi]
• Enhancing the Accuracy and Fairness of Human Decision MakingIsabel Valera, Adish Singla, Manuel Gomez-Rodriguez. 1774-1783 [doi]
• Temporal Regularization for Markov Decision ProcessPierre Thodoroff, Audrey Durand, Joelle Pineau, Doina Precup. 1784-1794 [doi]
• The Pessimistic Limits and Possibilities of Margin-based Losses in Semi-supervised LearningJesse H. Krijthe, Marco Loog. 1795-1804 [doi]
• Simple random search of static linear policies is competitive for reinforcement learningHoria Mania, Aurelia Guy, Benjamin Recht. 1805-1814 [doi]
• Generating Informative and Diverse Conversational Responses via Adversarial Information MaximizationYizhe Zhang, Michel Galley, Jianfeng Gao, Zhe Gan, Xiujun Li, Chris Brockett, Bill Dolan. 1815-1825 [doi]
• Entropy and mutual information in models of deep neural networksMarylou Gabrié, Andre Manoel, Clément Luneau, Jean Barbier, Nicolas Macris, Florent Krzakala, Lenka Zdeborová. 1826-1836 [doi]
• Collaborative Learning for Deep Neural NetworksGuocong Song, Wei Chai. 1837-1846 [doi]
• High Dimensional Linear Regression using Lattice Basis ReductionIlias Zadik, David Gamarnik. 1847-1857 [doi]
• Symbolic Graph Reasoning Meets ConvolutionsXiaodan Liang, Zhiting Hu, Hao Zhang, Liang Lin, Eric P. Xing. 1858-1868 [doi]
• DVAE#: Discrete Variational Autoencoders with Relaxed Boltzmann PriorsArash Vahdat, Evgeny Andriyash, William G. Macready. 1869-1878 [doi]
• Partially-Supervised Image CaptioningPeter Anderson 0001, Stephen Gould, Mark Johnson 0001. 1879-1890 [doi]
• 3D-Aware Scene Manipulation via Inverse GraphicsShunyu Yao, Tzu-Ming Harry Hsu, Jun-Yan Zhu, Jiajun Wu 0001, Antonio Torralba 0001, Bill Freeman, Josh Tenenbaum. 1891-1902 [doi]
• Random Feature Stein DiscrepanciesJonathan H. Huggins, Lester Mackey. 1903-1913 [doi]
• Distributed Stochastic Optimization via Adaptive SGDAshok Cutkosky, Róbert Busa-Fekete. 1914-1923 [doi]
• Precision and Recall for Time SeriesNesime Tatbul, Tae-Jun Lee, Stan Zdonik, Mejbah Alam, Justin Gottschlich. 1924-1934 [doi]
• Deep Attentive Tracking via Reciprocative LearningShi Pu, Yibing Song, Chao Ma 0004, Honggang Zhang, Ming-Hsuan Yang 0001. 1935-1945 [doi]
• Virtual Class Enhanced Discriminative Embedding LearningBinghui Chen, Weihong Deng, Haifeng Shen. 1946-1956 [doi]
• Attention in Convolutional LSTM for Gesture RecognitionLiang Zhang 0010, Guangming Zhu, Lin Mei, Peiyi Shen, Syed Afaq Ali Shah, Mohammed Bennamoun. 1957-1966 [doi]
• Pelee: A Real-Time Object Detection System on Mobile DevicesJun Wang, Tanner A. Bohn, Charles X. Ling. 1967-1976 [doi]
• Universal Growth in Production EconomiesSimina Brânzei, Ruta Mehta, Noam Nisan. 1975 [doi]
• Bayesian Model Selection Approach to Boundary Detection with Non-Local PriorsFei Jiang, Guosheng Yin, Francesca Dominici. 1978-1987 [doi]
• Efficient Stochastic Gradient Hard ThresholdingPan Zhou, Xiaotong Yuan, Jiashi Feng. 1988-1997 [doi]
• SplineNets: Continuous Neural Decision GraphsCem Keskin, Shahram Izadi. 1998-2008 [doi]
• Generalized Zero-Shot Learning with Deep Calibration NetworkShichen Liu, Mingsheng Long, Jianmin Wang 0001, Michael I. Jordan. 2009-2019 [doi]
• Neural Architecture Search with Bayesian Optimisation and Optimal TransportKirthevasan Kandasamy, Willie Neiswanger, Jeff Schneider, Barnabás Póczos, Eric P. Xing. 2020-2029 [doi]
• Embedding Logical Queries on Knowledge GraphsWilliam L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec. 2030-2041 [doi]
• Learning Optimal Reserve Price against Non-myopic BiddersJinyan Liu, Zhiyi Huang 0002, Xiangning Wang. 2042-2052 [doi]
• Sequential Context Encoding for Duplicate RemovalLu Qi, Shu Liu, Jianping Shi, Jiaya Jia. 2053-2062 [doi]
• Discovery of Latent 3D Keypoints via End-to-end Geometric ReasoningSupasorn Suwajanakorn, Noah Snavely, Jonathan J. Tompson, Mohammad Norouzi 0002. 2063-2074 [doi]
• Nonparametric learning from Bayesian models with randomized objective functionsSimon Lyddon, Stephen Walker, Chris C. Holmes. 2075-2085 [doi]
• SEGA: Variance Reduction via Gradient SketchingFilip Hanzely, Konstantin Mishchenko, Peter Richtárik. 2086-2097 [doi]
• Automatic Program Synthesis of Long Programs with a Learned Garbage CollectorAmit Zohar, Lior Wolf. 2098-2107 [doi]
• One-Shot Unsupervised Cross Domain TranslationSagie Benaim, Lior Wolf. 2108-2118 [doi]
• Regularizing by the Variance of the Activations' Sample-VariancesEtai Littwin, Lior Wolf. 2119-2129 [doi]
• Overlapping Clustering Models, and One (class) SVM to Bind Them AllXueyu Mao 0001, Purnamrita Sarkar, Deepayan Chakrabarti. 2130-2140 [doi]
• Algorithmic Linearly Constrained Gaussian ProcessesMarkus Lange-Hegermann. 2141-2152 [doi]
• DeepExposure: Learning to Expose Photos with Asynchronously Reinforced Adversarial LearningRunsheng Yu, Wenyu Liu, Yasen Zhang, Zhi Qu, Deli Zhao, Bo Zhang. 2153-2163 [doi]
• Norm matters: efficient and accurate normalization schemes in deep networksElad Hoffer, Ron Banner, Itay Golan, Daniel Soudry. 2164-2174 [doi]
• Dual Principal Component Pursuit: Improved Analysis and Efficient AlgorithmsZhihui Zhu, Yifan Wang, Daniel P. Robinson, Daniel Q. Naiman, René Vidal, Manolis C. Tsakiris. 2175-2185 [doi]
• MULAN: A Blind and Off-Grid Method for Multichannel Echo RetrievalHelena Peic Tukuljac, Antoine Deleforge, Rémi Gribonval. 2186-2196 [doi]
• Mixture Matrix CompletionDaniel L. Pimentel-Alarcón. 2197-2207 [doi]
• Trajectory Convolution for Action RecognitionYue Zhao, Yuanjun Xiong, Dahua Lin. 2208-2219 [doi]
• The Description Length of Deep Learning modelsLéonard Blier, Yann Ollivier. 2220-2230 [doi]
• A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit ProblemSampath Kannan, Jamie H. Morgenstern, Aaron Roth, Bo Waggoner, Zhiwei Steven Wu. 2231-2241 [doi]
• Revisiting Decomposable Submodular Function Minimization with Incidence RelationsPan Li, Olgica Milenkovic. 2242-2252 [doi]
• A Practical Algorithm for Distributed Clustering and Outlier DetectionJiecao Chen, Erfan Sadeqi Azer, Qin Zhang 0001. 2253-2262 [doi]
• Learning to Reconstruct Shapes from Unseen ClassesXiuming Zhang, Zhoutong Zhang, Chengkai Zhang, Josh Tenenbaum, Bill Freeman, Jiajun Wu 0001. 2263-2274 [doi]
• BourGAN: Generative Networks with Metric EmbeddingsChang Xiao, Peilin Zhong, Changxi Zheng. 2275-2286 [doi]
• Smoothed analysis of the low-rank approach for smooth semidefinite programsThomas Pumir, Samy Jelassi, Nicolas Boumal. 2287-2296 [doi]
• Zero-Shot Transfer with Deictic Object-Oriented Representation in Reinforcement LearningOfir Marom, Benjamin Rosman. 2297-2305 [doi]
• Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolateMikhail Belkin, Daniel J. Hsu, Partha Mitra. 2306-2317 [doi]
• Breaking the Span Assumption Yields Fast Finite-Sum MinimizationRobert Hannah, Yanli Liu, Daniel O'Connor, Wotao Yin. 2318-2327 [doi]
• Structured Local Minima in Sparse Blind DeconvolutionYuqian Zhang, Han-Wen Kuo, John Wright. 2328-2337 [doi]
• GIANT: Globally Improved Approximate Newton Method for Distributed OptimizationShusen Wang, Farbod Roosta-Khorasani, Peng Xu, Michael W. Mahoney. 2338-2348 [doi]
• Modelling sparsity, heterogeneity, reciprocity and community structure in temporal interaction dataXenia Miscouridou, Francois Caron, Yee Whye Teh. 2349-2358 [doi]
• Non-monotone Submodular Maximization in Exponentially Fewer IterationsEric Balkanski, Adam Breuer, Yaron Singer. 2359-2370 [doi]
• MetaGAN: An Adversarial Approach to Few-Shot LearningRuixiang Zhang, Tong Che, Zoubin Ghahramani, Yoshua Bengio, Yangqiu Song. 2371-2380 [doi]
• Local Differential Privacy for Evolving DataMatthew Joseph, Aaron Roth, Jonathan Ullman, Bo Waggoner. 2381-2390 [doi]
• Gaussian Process Conditional Density EstimationVincent Dutordoir, Hugh Salimbeni, James Hensman, Marc Peter Deisenroth. 2391-2401 [doi]
• Meta-Gradient Reinforcement LearningZhongwen Xu, Hado P. van Hasselt, David Silver. 2402-2413 [doi]
• Modular Networks: Learning to Decompose Neural ComputationLouis Kirsch, Julius Kunze, David Barber. 2414-2423 [doi]
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• Query Complexity of Bayesian Private LearningKuang Xu. 2436-2445 [doi]
• A theory on the absence of spurious solutions for nonconvex and nonsmooth optimizationCédric Josz, Yi Ouyang, Richard Y. Zhang, Javad Lavaei, Somayeh Sojoudi. 2446-2454 [doi]
• Recurrent World Models Facilitate Policy EvolutionDavid Ha, Jürgen Schmidhuber. 2455-2467 [doi]
• Ridge Regression and Provable Deterministic Ridge Leverage Score SamplingShannon R. McCurdy. 2468-2477 [doi]
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• How Does Batch Normalization Help Optimization?Shibani Santurkar, Dimitris Tsipras, Andrew Ilyas, Aleksander Madry. 2488-2498 [doi]
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• Tree-to-tree Neural Networks for Program TranslationXinyun Chen, Chang Liu, Dawn Song. 2552-2562 [doi]
• Batch-Instance Normalization for Adaptively Style-Invariant Neural NetworksHyeonseob Nam, Hyo-Eun Kim. 2563-2572 [doi]
• Structural Causal Bandits: Where to Intervene?Sanghack Lee, Elias Bareinboim. 2573-2583 [doi]
• Answerer in Questioner's Mind: Information Theoretic Approach to Goal-Oriented Visual DialogSang-Woo Lee, Yu-Jung Heo, Byoung-Tak Zhang. 2584-2594 [doi]
• A Unified Feature Disentangler for Multi-Domain Image Translation and ManipulationAlexander H. Liu, Yen-Cheng Liu, Yu-Ying Yeh, Yu-Chiang Frank Wang. 2595-2604 [doi]
• Online Learning with an Unknown Fairness MetricStephen Gillen, Christopher Jung, Michael J. Kearns, Aaron Roth. 2605-2614 [doi]
• Isolating Sources of Disentanglement in Variational AutoencodersTian Qi Chen, Xuechen Li, Roger B. Grosse, David K. Duvenaud. 2615-2625 [doi]
• Contextual bandits with surrogate losses: Margin bounds and efficient algorithmsDylan J. Foster, Akshay Krishnamurthy. 2626-2637 [doi]
• Representation Learning for Treatment Effect Estimation from Observational DataLiuyi Yao, Sheng Li 0001, Yaliang Li, Mengdi Huai, Jing Gao, Aidong Zhang. 2638-2648 [doi]
• Representation Balancing MDPs for Off-policy Policy EvaluationYao Liu, Omer Gottesman, Aniruddh Raghu, Matthieu Komorowski, Aldo A. Faisal, Finale Doshi-Velez, Emma Brunskill. 2649-2658 [doi]
• Out of the Box: Reasoning with Graph Convolution Nets for Factual Visual Question AnsweringMedhini Narasimhan, Svetlana Lazebnik, Alexander G. Schwing. 2659-2670 [doi]
• Causal Discovery from Discrete Data using Hidden Compact RepresentationRuichu Cai, Jie Qiao, Kun Zhang, Zhenjie Zhang, Zhifeng Hao. 2671-2679 [doi]
• Natasha 2: Faster Non-Convex Optimization Than SGDZeyuan Allen Zhu. 2680-2691 [doi]
• Minimax Statistical Learning with Wasserstein distancesJaeho Lee, Maxim Raginsky. 2692-2701 [doi]
• Provable Variational Inference for Constrained Log-Submodular ModelsJosip Djolonga, Stefanie Jegelka, Andreas Krause 0001. 2702-2712 [doi]
• Learning Hierarchical Semantic Image Manipulation through Structured RepresentationsSeunghoon Hong, Xinchen Yan, Thomas S. Huang, Honglak Lee. 2713-2723 [doi]
• Processing of missing data by neural networksMarek Smieja, Lukasz Struski, Jacek Tabor, Bartosz Zielinski 0001, Przemyslaw Spurek. 2724-2734 [doi]
• Safe Active Learning for Time-Series Modeling with Gaussian ProcessesChristoph Zimmer, Mona Meister, Duy Nguyen-Tuong. 2735-2744 [doi]
• Optimal Algorithms for Non-Smooth Distributed Optimization in NetworksKevin Scaman, Francis Bach, Sébastien Bubeck, Laurent Massoulié, Yin Tat Lee. 2745-2754 [doi]
• Computing Higher Order Derivatives of Matrix and Tensor ExpressionsSören Laue, Matthias Mitterreiter, Joachim Giesen. 2755-2764 [doi]
• Paraphrasing Complex Network: Network Compression via Factor TransferJangho Kim, Seonguk Park, Nojun Kwak. 2765-2774 [doi]
• Analytic solution and stationary phase approximation for the Bayesian lasso and elastic netTom Michoel. 2775-2785 [doi]
• Demystifying excessively volatile human learning: A Bayesian persistent prior and a neural approximationChaitanya Ryali, Gautam Reddy, Angela J. Yu. 2786-2795 [doi]
• Empirical Risk Minimization Under Fairness ConstraintsMichele Donini, Luca Oneto, Shai Ben-David, John Shawe-Taylor, Massimiliano Pontil. 2796-2806 [doi]
• Unsupervised Learning of Shape and Pose with Differentiable Point CloudsEldar Insafutdinov, Alexey Dosovitskiy. 2807-2817 [doi]
• Continuous-time Value Function Approximation in Reproducing Kernel Hilbert SpacesMotoya Ohnishi, Masahiro Yukawa, Mikael Johansson, Masashi Sugiyama. 2818-2829 [doi]
• Gradient Descent Meets Shift-and-Invert Preconditioning for Eigenvector ComputationZhiqiang Xu. 2830-2839 [doi]
• Factored BanditsJulian Zimmert, Yevgeny Seldin. 2840-2849 [doi]
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• Learning a High Fidelity Pose Invariant Model for High-resolution Face FrontalizationJie Cao, Yibo Hu, Hongwen Zhang, Ran He, Zhenan Sun. 2872-2882 [doi]
• Mirrored Langevin DynamicsYa-Ping Hsieh, Ali Kavis, Paul Rolland, Volkan Cevher. 2883-2892 [doi]
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• Stochastic Cubic Regularization for Fast Nonconvex OptimizationNilesh Tripuraneni, Mitchell Stern, Chi Jin, Jeffrey Regier, Michael I. Jordan. 2904-2913 [doi]
• Adaptation to Easy Data in Prediction with Limited AdviceTobias Sommer Thune, Yevgeny Seldin. 2914-2923 [doi]
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• Playing hard exploration games by watching YouTubeYusuf Aytar, Tobias Pfaff, David Budden, Thomas Paine, Ziyu Wang 0001, Nando de Freitas. 2935-2945 [doi]
• Dialog-to-Action: Conversational Question Answering Over a Large-Scale Knowledge BaseDaya Guo, Duyu Tang, Nan Duan, Ming Zhou, Jian Yin. 2946-2955 [doi]
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• Deep Generative Markov State ModelsHao Wu, Andreas Mardt, Luca Pasquali, Frank Noé. 3979-3988 [doi]
• Early Stopping for Nonparametric TestingMeimei Liu, Guang Cheng. 3989-3998 [doi]
• Solving Non-smooth Constrained Programs with Lower Complexity than \mathcal{O}(1/\varepsilon): A Primal-Dual Homotopy Smoothing ApproachXiaohan Wei, Hao Yu 0002, Qing Ling, Michael J. Neely. 3999-4009 [doi]
• Heterogeneous Bitwidth Binarization in Convolutional Neural NetworksJoshua Fromm, Shwetak Patel, Matthai Philipose. 4010-4019 [doi]
• Unsupervised Learning of Object Landmarks through Conditional Image GenerationTomas Jakab, Ankush Gupta, Hakan Bilen, Andrea Vedaldi. 4020-4031 [doi]
• Probabilistic Neural Programmed Networks for Scene GenerationZhiwei Deng, Jiacheng Chen, Yifang Fu, Greg Mori. 4032-4042 [doi]
• The streaming rollout of deep networks - towards fully model-parallel executionVolker Fischer, Jan Köhler, Thomas Pfeil. 4043-4054 [doi]
• KONG: Kernels for ordered-neighborhood graphsMoez Draief, Konstantin Kutzkov, Kevin Scaman, Milan Vojnovic. 4055-4064 [doi]
• GumBolt: Extending Gumbel trick to Boltzmann priorsAmir H. Khoshaman, Mohammad H. Amin. 4065-4074 [doi]
• Neural Networks Trained to Solve Differential Equations Learn General RepresentationsMartin Magill, Faisal Qureshi, Hendrick W. de Haan. 4075-4085 [doi]
• Beauty-in-averageness and its contextual modulations: A Bayesian statistical accountChaitanya Ryali, Angela J. Yu. 4086-4096 [doi]
• Distributed Weight Consolidation: A Brain Segmentation Case StudyPatrick McClure, Charles Y. Zheng, Jakub Kaczmarzyk, John Rogers-Lee, Satra Ghosh, Dylan Nielson, Peter A. Bandettini, Francisco Pereira. 4097-4107 [doi]
• Efficient Projection onto the Perfect Phylogeny ModelBei Jia, Surjyendu Ray, Sam Safavi, José Bento. 4108-4118 [doi]
• TETRIS: TilE-matching the TRemendous Irregular SparsityYu Ji, Ling Liang, Lei Deng, Youyang Zhang, Youhui Zhang, Yuan Xie. 4119-4129 [doi]
• Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classificationHarsh Shrivastava, Eugene Bart, Bob Price, Hanjun Dai, Bo Dai, Srinivas Aluru. 4130-4140 [doi]
• Differentially Private Robust Low-Rank ApproximationRaman Arora, Vladimir Braverman, Jalaj Upadhyay. 4141-4149 [doi]
• Meta-Learning MCMC ProposalsTongzhou Wang, Yi Wu, Dave Moore, Stuart J. Russell. 4150-4160 [doi]
• An Information-Theoretic Analysis for Thompson Sampling with Many ActionsShi Dong, Benjamin Van Roy. 4161-4169 [doi]
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• Bilevel Distance Metric Learning for Robust Image RecognitionJie Xu, Lei Luo, Cheng Deng, Heng Huang. 4202-4211 [doi]
• Differentially Private Uniformly Most Powerful Tests for Binomial DataJordan Awan, Aleksandra Slavkovic. 4212-4222 [doi]
• Scalable Coordinated Exploration in Concurrent Reinforcement LearningMaria Dimakopoulou, Ian Osband, Benjamin Van Roy. 4223-4232 [doi]
• Integrated accounts of behavioral and neuroimaging data using flexible recurrent neural network modelsAmir Dezfouli, Richard W. Morris, Fabio T. Ramos, Peter Dayan, Bernard W. Balleine. 4233-4242 [doi]
• BML: A High-performance, Low-cost Gradient Synchronization Algorithm for DML TrainingSongtao Wang, Dan Li, Yang Cheng, Jinkun Geng, Yanshu Wang, Shuai Wang, Shu-Tao Xia, Jianping Wu. 4243-4253 [doi]
• Inexact trust-region algorithms on Riemannian manifoldsHiroyuki Kasai, Bamdev Mishra. 4254-4265 [doi]
• Can We Gain More from Orthogonality Regularizations in Training Deep Networks?Nitin Bansal, Xiaohan Chen, Zhangyang Wang. 4266-4276 [doi]
• Binary Rating Estimation with Graph Side InformationKwangjun Ahn, Kangwook Lee, Hyunseung Cha, Changho Suh. 4277-4288 [doi]
• SimplE Embedding for Link Prediction in Knowledge GraphsSeyed Mehran Kazemi, David Poole 0001. 4289-4300 [doi]
• Differentially Private Contextual Linear BanditsRoshan Shariff, Or Sheffet. 4301-4311 [doi]
• Submodular Field Grammars: Representation, Inference, and Application to Image ParsingAbram L. Friesen, Pedro M. Domingos. 4312-4322 [doi]
• A Bridging Framework for Model Optimization and Deep PropagationRisheng Liu, Shichao Cheng, Xiaokun Liu, Long Ma, Xin Fan, Zhongxuan Luo. 4323-4332 [doi]
• Completing State Representations using Spectral LearningNan Jiang, Alex Kulesza, Satinder P. Singh. 4333-4342 [doi]
• Optimization of Smooth Functions with Noisy Observations: Local Minimax RatesYining Wang, Sivaraman Balakrishnan, Aarti Singh. 4343-4354 [doi]
• Adding One Neuron Can Eliminate All Bad Local MinimaShiyu Liang, Ruoyu Sun, Jason D. Lee, R. Srikant. 4355-4365 [doi]
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• The Physical Systems Behind Optimization AlgorithmsLin Yang, Raman Arora, Vladimir Braverman, Tuo Zhao. 4377-4386 [doi]
• Mallows Models for Top-k ListsFlavio Chierichetti, Anirban Dasgupta 0001, Shahrzad Haddadan, Ravi Kumar 0001, Silvio Lattanzi. 4387-4397 [doi]
• Amortized Inference RegularizationRui Shu, Hung H. Bui, Shengjia Zhao, Mykel J. Kochenderfer, Stefano Ermon. 4398-4407 [doi]
• Maximum Causal Tsallis Entropy Imitation LearningKyungjae Lee, Sungjoon Choi, Songhwai Oh. 4408-4418 [doi]
• Limited Memory Kelley's Method Converges for Composite Convex and Submodular ObjectivesSong Zhou, Swati Gupta, Madeleine Udell. 4419-4429 [doi]
• Semi-Supervised Learning with Declaratively Specified Entropy ConstraintsHaitian Sun, William W. Cohen, Lidong Bing. 4430-4440 [doi]
• End-to-end Symmetry Preserving Inter-atomic Potential Energy Model for Finite and Extended SystemsLinfeng Zhang, Jiequn Han, Han Wang, Wissam Saidi, Roberto Car, Weinan E. 4441-4451 [doi]
• Sparsified SGD with MemorySebastian U. Stich, Jean-Baptiste Cordonnier, Martin Jaggi. 4452-4463 [doi]
• Exponentiated Strongly Rayleigh DistributionsZelda E. Mariet, Suvrit Sra, Stefanie Jegelka. 4464-4474 [doi]
• Importance Weighting and Variational InferenceJustin Domke, Daniel R. Sheldon. 4475-4484 [doi]
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• Expanding Holographic Embeddings for Knowledge CompletionYexiang Xue, Yang Yuan, Zhitian Xu, Ashish Sabharwal. 4496-4506 [doi]
• Lifelong Inverse Reinforcement LearningJorge Armando Mendez Mendez, Shashank Shivkumar, Eric Eaton. 4507-4518 [doi]
• Explaining Deep Learning Models - A Bayesian Non-parametric ApproachWenbo Guo, Sui Huang, Yunzhe Tao, Xinyu Xing, Lin Lin. 4519-4529 [doi]
• Third-order Smoothness Helps: Faster Stochastic Optimization Algorithms for Finding Local MinimaYaodong Yu, Pan Xu, Quanquan Gu. 4530-4540 [doi]
• COLA: Decentralized Linear LearningLie He, An Bian, Martin Jaggi. 4541-4551 [doi]
• MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive HealthcareEdward Choi, Cao Xiao, Walter F. Stewart, Jimeng Sun. 4552-4562 [doi]
• Adaptive Sampling Towards Fast Graph Representation LearningWen-bing Huang, Tong Zhang 0001, Yu Rong, JunZhou Huang. 4563-4572 [doi]
• Hunting for Discriminatory Proxies in Linear Regression ModelsSamuel Yeom, Anupam Datta, Matt Fredrikson. 4573-4583 [doi]
• Towards Robust Detection of Adversarial ExamplesTianyu Pang, Chao Du, Yinpeng Dong, Jun Zhu. 4584-4594 [doi]
• Active MattingXin Yang, Ke Xu, Shaozhe Chen, Shengfeng He, Baocai Yin, Rynson W. H. Lau. 4595-4605 [doi]
• Learning filter widths of spectral decompositions with waveletsHaidar Khan, Bülent Yener. 4606-4617 [doi]
• Byzantine Stochastic Gradient DescentDan Alistarh, Zeyuan Allen Zhu, Jerry Li 0001. 4618-4628 [doi]
• PG-TS: Improved Thompson Sampling for Logistic Contextual BanditsBianca Dumitrascu, Karen Feng, Barbara E. Engelhardt. 4629-4638 [doi]
• Spectral Filtering for General Linear Dynamical SystemsElad Hazan, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang. 4639-4648 [doi]
• On Learning Intrinsic Rewards for Policy Gradient MethodsZeyu Zheng, Junhyuk Oh, Satinder Singh. 4649-4659 [doi]
• Boolean Decision Rules via Column GenerationSanjeeb Dash, Oktay Günlük, Dennis Wei. 4660-4670 [doi]
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• Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound ConditionsMingrui Liu, Xiaoxuan Zhang, Lijun Zhang, Jing Rong, Tianbao Yang. 4683-4694 [doi]
• Learning Bounds for Greedy Approximation with Explicit Feature Maps from Multiple KernelsShahin Shahrampour, Vahid Tarokh. 4695-4706 [doi]
• A Mathematical Model For Optimal Decisions In A Representative DemocracyMalik Magdon-Ismail, Lirong Xia. 4707-4716 [doi]
• Negotiable Reinforcement Learning for Pareto Optimal Sequential Decision-MakingNishant Desai, Andrew Critch, Stuart J. Russell. 4717-4725 [doi]
• Non-metric Similarity Graphs for Maximum Inner Product SearchStanislav Morozov, Artem Babenko. 4726-4735 [doi]
• Recurrently Controlled Recurrent NetworksYi Tay, Anh Tuan Luu, Siu Cheung Hui. 4736-4748 [doi]
• Fast greedy algorithms for dictionary selection with generalized sparsity constraintsKaito Fujii, Tasuku Soma. 4749-4758 [doi]
• Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics ModelsKurtland Chua, Roberto Calandra, Rowan McAllister, Sergey Levine. 4759-4770 [doi]
• A Smoother Way to Train Structured Prediction ModelsVenkata Krishna Pillutla, Vincent Roulet, Sham M. Kakade, Zaïd Harchaoui. 4771-4783 [doi]
• Context-dependent upper-confidence bounds for directed explorationRaksha Kumaraswamy, Matthew Schlegel, Adam White, Martha White. 4784-4794 [doi]
• A Unified View of Piecewise Linear Neural Network VerificationRudy R. Bunel, Ilker Turkaslan, Philip H. S. Torr, Pushmeet Kohli, Pawan Kumar Mudigonda. 4795-4804 [doi]
• Hierarchical Graph Representation Learning with Differentiable PoolingZhitao Ying, Jiaxuan You, Christopher Morris 0001, Xiang Ren, William L. Hamilton, Jure Leskovec. 4805-4815 [doi]
• Non-Ergodic Alternating Proximal Augmented Lagrangian Algorithms with Optimal RatesQuoc Tran-Dinh. 4816-4824 [doi]
• Information-based Adaptive Stimulus Selection to Optimize Communication Efficiency in Brain-Computer InterfacesBoyla Mainsah, Dmitry Kalika, Leslie M. Collins, Siyuan Liu, Chandra S. Throckmorton. 4825-4835 [doi]
• Porcupine Neural Networks: Approximating Neural Network LandscapesSoheil Feizi, Hamid Javadi, Jesse Zhang, David Tse. 4836-4846 [doi]
• Fairness Through Computationally-Bounded AwarenessMichael P. Kim, Omer Reingold, Guy N. Rothblum. 4847-4857 [doi]
• Adaptive Negative Curvature Descent with Applications in Non-convex OptimizationMingrui Liu, Zhe Li, Xiaoyu Wang, Jinfeng Yi, Tianbao Yang. 4858-4867 [doi]
• Is Q-Learning Provably Efficient?Chi Jin, Zeyuan Allen Zhu, Sébastien Bubeck, Michael I. Jordan. 4868-4878 [doi]
• Interpreting Neural Network Judgments via Minimal, Stable, and Symbolic CorrectionsXin Zhang, Armando Solar-Lezama, Rishabh Singh. 4879-4890 [doi]
• Measures of distortion for machine learningLeena Chennuru Vankadara, Ulrike von Luxburg. 4891-4900 [doi]
• On the Local Minima of the Empirical RiskChi Jin, Lydia T. Liu, Rong Ge 0001, Michael I. Jordan. 4901-4910 [doi]
• Densely Connected Attention Propagation for Reading ComprehensionYi Tay, Anh Tuan Luu, Siu Cheung Hui, Jian Su. 4911-4922 [doi]
• Bandit Learning with Positive ExternalitiesVirag Shah, Jose Blanchet, Ramesh Johari. 4923-4933 [doi]
• Learning Confidence Sets using Support Vector MachinesWenbo Wang, Xingye Qiao. 4934-4943 [doi]
• Efficient Neural Network Robustness Certification with General Activation FunctionsHuan Zhang, Tsui-Wei Weng, Pin-Yu Chen, Cho-Jui Hsieh, Luca Daniel. 4944-4953 [doi]
• Hessian-based Analysis of Large Batch Training and Robustness to AdversariesZhewei Yao, Amir Gholami, Qi Lei, Kurt Keutzer, Michael W. Mahoney. 4954-4964 [doi]
• Neural Edit Operations for Biological SequencesSatoshi Koide, Keisuke Kawano, Takuro Kutsuna. 4965-4975 [doi]
• Objective and efficient inference for couplings in neuronal networksYu Terada, Tomoyuki Obuchi, Takuya Isomura, Yoshiyuki Kabashima. 4976-4985 [doi]
• Learning from Group Comparisons: Exploiting Higher Order InteractionsYao Li, Minhao Cheng, Kevin Fujii, Fushing Hsieh, Cho-Jui Hsieh. 4986-4995 [doi]
• Supervising Unsupervised LearningVikas Garg. 4996-5006 [doi]
• Nonparametric Bayesian Lomax delegate racing for survival analysis with competing risksQuan Zhang, Mingyuan Zhou. 5007-5018 [doi]
• Adversarially Robust Generalization Requires More DataLudwig Schmidt, Shibani Santurkar, Dimitris Tsipras, Kunal Talwar, Aleksander Madry. 5019-5031 [doi]
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• Practical exact algorithm for trembling-hand equilibrium refinements in gamesGabriele Farina, Nicola Gatti 0001, Tuomas Sandholm. 5044-5054 [doi]
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• Middle-Out DecodingShikib Mehri, Leonid Sigal. 5523-5534 [doi]
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• Multimodal Generative Models for Scalable Weakly-Supervised LearningMike Wu, Noah Goodman. 5580-5590 [doi]
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• The Convergence of Sparsified Gradient MethodsDan Alistarh, Torsten Hoefler, Mikael Johansson 0001, Nikola Konstantinov, Sarit Khirirat, Cédric Renggli. 5977-5987 [doi]
• Automating Bayesian optimization with Bayesian optimizationGustavo Malkomes, Roman Garnett. 5988-5997 [doi]
• Stacked Semantics-Guided Attention Model for Fine-Grained Zero-Shot LearningYunlong Yu, Zhong Ji, Yanwei Fu, Jichang Guo, Yanwei Pang, Zhongfei (Mark) Zhang. 5998-6007 [doi]
• Dirichlet-based Gaussian Processes for Large-scale Calibrated ClassificationDimitrios Milios, Raffaello Camoriano, Pietro Michiardi, Lorenzo Rosasco, Maurizio Filippone. 6008-6018 [doi]
• Multi-Task Zipping via Layer-wise Neuron SharingXiaoxi He, Zimu Zhou, Lothar Thiele. 6019-6029 [doi]
• Dimensionally Tight Bounds for Second-Order Hamiltonian Monte CarloOren Mangoubi, Nisheeth K. Vishnoi. 6030-6040 [doi]
• Approximation algorithms for stochastic clusteringDavid G. Harris, Shi Li, Aravind Srinivasan, Khoa Trinh, Thomas Pensyl. 6041-6050 [doi]
• Evolutionary Stochastic Gradient Descent for Optimization of Deep Neural NetworksXiaodong Cui, Wei Zhang, Zoltán Tüske, Michael Picheny. 6051-6061 [doi]
• Learning to Infer Graphics Programs from Hand-Drawn ImagesKevin Ellis, Daniel Ritchie, Armando Solar-Lezama, Josh Tenenbaum. 6062-6071 [doi]
• Graphical Generative Adversarial NetworksChongxuan Li, Max Welling, Jun Zhu 0001, Bo Zhang. 6072-6083 [doi]
• Variational Learning on Aggregate Outputs with Gaussian ProcessesHo Chung Leon Law, Dino Sejdinovic, Ewan Cameron, Tim C. D. Lucas, Seth R. Flaxman, Katherine Battle, Kenji Fukumizu. 6084-6094 [doi]
• MacNet: Transferring Knowledge from Machine Comprehension to Sequence-to-Sequence ModelsBoyuan Pan, Yazheng Yang, Hao Li, Zhou Zhao, Yueting Zhuang, Deng Cai, Xiaofei He. 6095-6105 [doi]
• Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural NetworksAli Shafahi, W. Ronny Huang, Mahyar Najibi, Octavian Suciu, Christoph Studer, Tudor Dumitras, Tom Goldstein. 6106-6116 [doi]
• Information Constraints on Auto-Encoding Variational BayesRomain Lopez, Jeffrey Regier, Michael I. Jordan, Nir Yosef. 6117-6128 [doi]
• Recurrent Transformer Networks for Semantic CorrespondenceSeungryong Kim, Stephen Lin, Sangryul Jeon, Dongbo Min, Kwanghoon Sohn. 6129-6139 [doi]
• Online convex optimization for cumulative constraintsJianjun Yuan, Andrew G. Lamperski. 6140-6149 [doi]
• Predict Responsibly: Improving Fairness and Accuracy by Learning to DeferDavid Madras, Toniann Pitassi, Richard S. Zemel. 6150-6160 [doi]
• Deep State Space Models for Unconditional Word GenerationFlorian Schmidt, Thomas Hofmann. 6161-6171 [doi]
• ResNet with one-neuron hidden layers is a Universal ApproximatorHongzhou Lin, Stefanie Jegelka. 6172-6181 [doi]
• Transfer of Value Functions via Variational MethodsAndrea Tirinzoni, Rafael Rodríguez-Sánchez, Marcello Restelli. 6182-6192 [doi]
• The Cluster Description Problem - Complexity Results, Formulations and ApproximationsIan Davidson, Antoine Gourru, S. S. Ravi. 6193-6203 [doi]
• Sharp Bounds for Generalized Uniformity TestingIlias Diakonikolas, Daniel M. Kane, Alistair Stewart. 6204-6213 [doi]
• Deep Neural Networks with Box ConvolutionsEgor Burkov, Victor S. Lempitsky. 6214-6224 [doi]
• Learning towards Minimum Hyperspherical EnergyWeiyang Liu, Rongmei Lin, Zhen Liu, Lixin Liu, Zhiding Yu, Bo Dai, Le Song. 6225-6236 [doi]
• LF-Net: Learning Local Features from ImagesYuki Ono, Eduard Trulls, Pascal Fua, Kwang Moo Yi. 6237-6247 [doi]
• SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural GradientAaron Mishkin, Frederik Kunstner, Didrik Nielsen, Mark W. Schmidt, Mohammad Emtiyaz Khan. 6248-6258 [doi]
• Tangent: Automatic differentiation using source-code transformation for dynamically typed array programmingBart van Merrienboer, Dan Moldovan, Alexander B. Wiltschko. 6259-6268 [doi]
• Multi-domain Causal Structure Learning in Linear SystemsAmirEmad Ghassami, Negar Kiyavash, Biwei Huang, Kun Zhang. 6269-6279 [doi]
• Privacy Amplification by Subsampling: Tight Analyses via Couplings and DivergencesBorja Balle, Gilles Barthe, Marco Gaboardi. 6280-6290 [doi]
• Exponentially Weighted Imitation Learning for Batched Historical DataQing Wang, Jiechao Xiong, Lei Han, Peng Sun, Han Liu, Tong Zhang. 6291-6300 [doi]
• Algebraic tests of general Gaussian latent tree modelsDennis Leung, Mathias Drton. 6301-6310 [doi]
• Navigating with Graph Representations for Fast and Scalable Decoding of Neural Language ModelsMinjia Zhang, Wenhan Wang, Xiaodong Liu, Jianfeng Gao, Yuxiong He. 6311-6322