Abstract is missing.
- Wider and Deeper, Cheaper and Faster: Tensorized LSTMs for Sequence LearningZhen He, Shaobing Gao, Liang Xiao, Daxue Liu, Hangen He, David Barber. 1-11 [doi]
- Concentration of Multilinear Functions of the Ising Model with Applications to Network DataConstantinos Daskalakis, Nishanth Dikkala, Gautam C. Kamath. 12-22 [doi]
- Deep Subspace Clustering NetworksPan Ji, Tong Zhang, Hongdong Li, Mathieu Salzmann, Ian D. Reid 0001. 23-32 [doi]
- Attentional Pooling for Action RecognitionRohit Girdhar, Deva Ramanan. 33-44 [doi]
- On the Consistency of Quick ShiftHeinrich Jiang. 45-54 [doi]
- Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite OptimizationFabian Pedregosa, Rémi Leblond, Simon Lacoste-Julien. 55-64 [doi]
- Dual-Agent GANs for Photorealistic and Identity Preserving Profile Face SynthesisJian Zhao, Lin Xiong, Jayashree Karlekar, Jianshu Li, Fang Zhao 0006, Zhecan Wang, Sugiri Pranata, Shengmei Shen, Shuicheng Yan, Jiashi Feng. 65-75 [doi]
- Dilated Recurrent Neural NetworksShiyu Chang, Yang Zhang, Wei Han, Mo Yu, Xiaoxiao Guo, Wei Tan, Xiaodong Cui, Michael J. Witbrock, Mark A. Hasegawa-Johnson, Thomas S. Huang. 76-86 [doi]
- Hunt For The Unique, Stable, Sparse And Fast Feature Learning On GraphsSaurabh Verma, Zhi-Li Zhang. 87-97 [doi]
- Scalable Generalized Linear Bandits: Online Computation and HashingKwang-Sung Jun, Aniruddha Bhargava, Robert D. Nowak, Rebecca Willett. 98-108 [doi]
- Probabilistic Models for Integration Error in the Assessment of Functional Cardiac ModelsChris J. Oates, Steven Niederer, Angela Lee, François-Xavier Briol, Mark A. Girolami. 109-117 [doi]
- Machine Learning with Adversaries: Byzantine Tolerant Gradient DescentPeva Blanchard, El Mahdi El Mhamdi, Rachid Guerraoui, Julien Stainer. 118-128 [doi]
- Dynamic Safe Interruptibility for Decentralized Multi-Agent Reinforcement LearningEl Mahdi El Mhamdi, Rachid Guerraoui, Hadrien Hendrikx, Alexandre Maurer. 129-139 [doi]
- Interactive Submodular BanditLin Chen 0003, Andreas Krause 0001, Amin Karbasi. 140-151 [doi]
- Learning to See Physics via Visual De-animationJiajun Wu 0001, Erika Lu, Pushmeet Kohli, Bill Freeman, Josh Tenenbaum. 152-163 [doi]
- Label Efficient Learning of Transferable Representations acrosss Domains and TasksZelun Luo, Yuliang Zou, Judy Hoffman, Fei-Fei Li. 164-176 [doi]
- Decoding with Value Networks for Neural Machine TranslationDi He, Hanqing Lu, Yingce Xia, Tao Qin, Liwei Wang 0001, Tie-Yan Liu. 177-186 [doi]
- Parametric Simplex Method for Sparse LearningHaotian Pang, Han Liu, Robert J. Vanderbei, Tuo Zhao. 187-196 [doi]
- Group Sparse Additive MachineHong Chen, Xiaoqian Wang, Cheng Deng, Heng Huang. 197-207 [doi]
- Uprooting and Rerooting Higher-Order Graphical ModelsMark Rowland, Adrian Weller. 208-217 [doi]
- The Unreasonable Effectiveness of Structured Random Orthogonal EmbeddingsKrzysztof Marcin Choromanski, Mark Rowland, Adrian Weller. 218-227 [doi]
- From Parity to Preference-based Notions of Fairness in ClassificationMuhammad Bilal Zafar, Isabel Valera, Manuel Gomez-Rodriguez, Krishna P. Gummadi, Adrian Weller. 228-238 [doi]
- Inferring Generative Model Structure with Static AnalysisParoma Varma, Bryan D. He, Payal Bajaj, Nishith Khandwala, Imon Banerjee, Daniel L. Rubin, Christopher Ré. 239-249 [doi]
- Structured Embedding Models for Grouped DataMaja R. Rudolph, Francisco J. R. Ruiz, Susan Athey, David M. Blei. 250-260 [doi]
- A Linear-Time Kernel Goodness-of-Fit TestWittawat Jitkrittum, Wenkai Xu, Zoltán Szabó 0001, Kenji Fukumizu, Arthur Gretton. 261-270 [doi]
- Cortical microcircuits as gated-recurrent neural networksRui Costa, Ioannis Alexandros M. Assael, Brendan Shillingford, Nando de Freitas, TIm Vogels. 271-282 [doi]
- k-Support and Ordered Weighted Sparsity for Overlapping Groups: Hardness and AlgorithmsCong Han Lim, Stephen J. Wright. 283-291 [doi]
- A simple model of recognition and recall memoryNisheeth Srivastava, Edward Vul. 292-300 [doi]
- On Structured Prediction Theory with Calibrated Convex Surrogate LossesAnton Osokin, Francis R. Bach, Simon Lacoste-Julien. 301-312 [doi]
- Best of Both Worlds: Transferring Knowledge from Discriminative Learning to a Generative Visual Dialog ModelJiasen Lu, Anitha Kannan, Jianwei Yang, Devi Parikh, Dhruv Batra. 313-323 [doi]
- MaskRNN: Instance Level Video Object SegmentationYuan-Ting Hu, Jia-Bin Huang, Alexander G. Schwing. 324-333 [doi]
- Gated Recurrent Convolution Neural Network for OCRJianfeng Wang, Xiaolin Hu. 334-343 [doi]
- Towards Accurate Binary Convolutional Neural NetworkXiaofan Lin, Cong Zhao, Wei Pan. 344-352 [doi]
- Semi-Supervised Learning for Optical Flow with Generative Adversarial NetworksWei-Sheng Lai, Jia-Bin Huang, Ming-Hsuan Yang 0001. 353-363 [doi]
- Learning a Multi-View Stereo MachineAbhishek Kar, Christian Häne, Jitendra Malik. 364-375 [doi]
- Phase Transitions in the Pooled Data ProblemJonathan Scarlett, Volkan Cevher. 376-384 [doi]
- Universal Style Transfer via Feature TransformsYijun Li, Chen Fang, Jimei Yang, Zhaowen Wang, Xin Lu, Ming-Hsuan Yang. 385-395 [doi]
- On the Model Shrinkage Effect of Gamma Process Edge Partition ModelsIku Ohama, Issei Sato, Takuya Kida, Hiroki Arimura. 396-404 [doi]
- Pose Guided Person Image GenerationLiqian Ma, Xu Jia, Qianru Sun, Bernt Schiele, Tinne Tuytelaars, Luc Van Gool. 405-415 [doi]
- Inference in Graphical Models via Semidefinite Programming HierarchiesMurat A. Erdogdu, Yash Deshpande, Andrea Montanari. 416-424 [doi]
- Variable Importance Using Decision TreesJalil Kazemitabar, Arash Amini, Adam Bloniarz, Ameet S. Talwalkar. 425-434 [doi]
- Preventing Gradient Explosions in Gated Recurrent UnitsSekitoshi Kanai, Yasuhiro Fujiwara, Sotetsu Iwamura. 435-444 [doi]
- On the Power of Truncated SVD for General High-rank Matrix Estimation ProblemsSimon S. Du, Yining Wang, Aarti Singh. 445-455 [doi]
- f-GANs in an Information Geometric NutshellRichard Nock, Zac Cranko, Aditya Krishna Menon, Lizhen Qu, Robert C. Williamson. 456-464 [doi]
- Toward Multimodal Image-to-Image TranslationJun-Yan Zhu, Richard Zhang, Deepak Pathak, Trevor Darrell, Alexei A. Efros, Oliver Wang, Eli Shechtman. 465-476 [doi]
- Mixture-Rank Matrix Approximation for Collaborative FilteringDongsheng Li, Chao Chen, Wei Liu, Tun Lu, Ning Gu, Stephen M. Chu. 477-485 [doi]
- Non-monotone Continuous DR-submodular Maximization: Structure and AlgorithmsAndrew An Bian, Kfir Yehuda Levy, Andreas Krause 0001, Joachim M. Buhmann. 486-496 [doi]
- Learning with Average Top-k LossYanbo Fan, Siwei Lyu, Yiming Ying, Bao-Gang Hu. 497-505 [doi]
- Learning multiple visual domains with residual adaptersSylvestre-Alvise Rebuffi, Hakan Bilen, Andrea Vedaldi. 506-516 [doi]
- Dykstra's Algorithm, ADMM, and Coordinate Descent: Connections, Insights, and ExtensionsRyan J. Tibshirani. 517-528 [doi]
- Learning Spherical Convolution for Fast Features from 360° ImageryYu-Chuan Su, Kristen Grauman. 529-539 [doi]
- MarrNet: 3D Shape Reconstruction via 2.5D SketchesJiajun Wu 0001, Yifan Wang, Tianfan Xue, Xingyuan Sun, Bill Freeman, Josh Tenenbaum. 540-550 [doi]
- Multimodal Learning and Reasoning for Visual Question AnsweringIlija Ilievski, Jiashi Feng. 551-562 [doi]
- Adversarial Surrogate Losses for Ordinal RegressionRizal Fathony, Mohammad Ali Bashiri, Brian D. Ziebart. 563-573 [doi]
- Hypothesis Transfer Learning via Transformation FunctionsSimon S. Du, Jayanth Koushik, Aarti Singh, Barnabás Póczos. 574-584 [doi]
- Controllable Invariance through Adversarial Feature LearningQizhe Xie, Zihang Dai, Yulun Du, Eduard H. Hovy, Graham Neubig. 585-596 [doi]
- Convergence Analysis of Two-layer Neural Networks with ReLU ActivationYuanzhi Li, Yang Yuan. 597-607 [doi]
- Doubly Accelerated Stochastic Variance Reduced Dual Averaging Method for Regularized Empirical Risk MinimizationTomoya Murata, Taiji Suzuki. 608-617 [doi]
- Langevin Dynamics with Continuous Tempering for Training Deep Neural NetworksNanyang Ye, Zhanxing Zhu, Rafal Mantiuk. 618-626 [doi]
- Efficient Online Linear Optimization with Approximation AlgorithmsDan Garber. 627-635 [doi]
- Geometric Descent Method for Convex Composite MinimizationShixiang Chen, Shiqian Ma, Wei Liu. 636-644 [doi]
- Diffusion Approximations for Online Principal Component Estimation and Global ConvergenceChris Junchi Li, Mengdi Wang, Tong Zhang. 645-655 [doi]
- Avoiding Discrimination through Causal ReasoningNiki Kilbertus, Mateo Rojas-Carulla, Giambattista Parascandolo, Moritz Hardt, Dominik Janzing, Bernhard Schölkopf. 656-666 [doi]
- Nonparametric Online Regression while Learning the MetricIlja Kuzborskij, Nicolò Cesa-Bianchi. 667-676 [doi]
- Recycling Privileged Learning and Distribution Matching for FairnessNovi Quadrianto, Viktoriia Sharmanska. 677-688 [doi]
- Safe and Nested Subgame Solving for Imperfect-Information GamesNoam Brown, Tuomas Sandholm. 689-699 [doi]
- Unsupervised Image-to-Image Translation NetworksMing-Yu Liu, Thomas Breuel, Jan Kautz. 700-708 [doi]
- Coded Distributed Computing for Inverse ProblemsYaoqing Yang, Pulkit Grover, Soummya Kar. 709-719 [doi]
- A Screening Rule for l1-Regularized Ising Model EstimationZhaobin Kuang, Sinong Geng, David Page. 720-731 [doi]
- Improved Dynamic Regret for Non-degenerate FunctionsLijun Zhang 0005, Tianbao Yang, Jinfeng Yi, Jing Rong, Zhi-Hua Zhou. 732-741 [doi]
- Learning Efficient Object Detection Models with Knowledge DistillationGuobin Chen, Wongun Choi, Xiang Yu, Tony X. Han, Manmohan Chandraker. 742-751 [doi]
- One-Sided Unsupervised Domain MappingSagie Benaim, Lior Wolf. 752-762 [doi]
- Deep Mean-Shift Priors for Image RestorationSiavash Arjomand Bigdeli, Matthias Zwicker, Paolo Favaro, Meiguang Jin. 763-772 [doi]
- Greedy Algorithms for Cone Constrained Optimization with Convergence GuaranteesFrancesco Locatello, Michael Tschannen, Gunnar Rätsch, Martin Jaggi. 773-784 [doi]
- A New Theory for Matrix CompletionGuangcan Liu, Qingshan Liu, Xiaotong Yuan. 785-794 [doi]
- Robust Hypothesis Test for Nonlinear Effect with Gaussian ProcessesJeremiah Liu, Brent Coull. 795-803 [doi]
- Lower bounds on the robustness to adversarial perturbationsJonathan Peck, Joris Roels, Bart Goossens, Yvan Saeys. 804-813 [doi]
- Minimizing a Submodular Function from SamplesEric Balkanski, Yaron Singer. 814-822 [doi]
- Introspective Classification with Convolutional NetsLong Jin, Justin Lazarow, Zhuowen Tu. 823-833 [doi]
- Label Distribution Learning ForestsWei Shen, Kai Zhao, Yilu Guo, Alan L. Yuille. 834-843 [doi]
- Unsupervised learning of object frames by dense equivariant image labellingJames Thewlis, Hakan Bilen, Andrea Vedaldi. 844-855 [doi]
- Compression-aware Training of Deep NetworksJose M. Alvarez, Mathieu Salzmann. 856-867 [doi]
- Multiscale Semi-Markov Dynamics for Intracortical Brain-Computer InterfacesDaniel Milstein, Jason Pacheco, Leigh J. Hochberg, John D. Simeral, Beata Jarosiewicz, Erik B. Sudderth. 868-878 [doi]
- PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMsYunbo Wang, Mingsheng Long, Jianmin Wang, Zhifeng Gao, Philip S. Yu. 879-888 [doi]
- Detrended Partial Cross Correlation for Brain Connectivity AnalysisJaime S. Ide, Fabio Augusto Cappabianco, Fábio Augusto Faria, Chiang-Shan R. Li. 889-897 [doi]
- Contrastive Learning for Image CaptioningBo Dai, Dahua Lin. 898-907 [doi]
- Safe Model-based Reinforcement Learning with Stability GuaranteesFelix Berkenkamp, Matteo Turchetta, Angela P. Schoellig, Andreas Krause 0001. 908-919 [doi]
- Online multiclass boostingYoung-Hun Jung, Jack Goetz, Ambuj Tewari. 920-929 [doi]
- Matching on Balanced Nonlinear Representations for Treatment Effects EstimationSheng Li 0001, Yun Fu. 930-940 [doi]
- Learning Overcomplete HMMsVatsal Sharan, Sham M. Kakade, Percy S. Liang, Gregory Valiant. 941-950 [doi]
- GP CaKe: Effective brain connectivity with causal kernelsLuca Ambrogioni, Max Hinne, Marcel van Gerven, Eric Maris. 951-960 [doi]
- Decoupling "when to update" from "how to update"Eran Malach, Shai Shalev-Shwartz. 961-971 [doi]
- Self-Normalizing Neural NetworksGünter Klambauer, Thomas Unterthiner, Andreas Mayr, Sepp Hochreiter. 972-981 [doi]
- Learning to Pivot with Adversarial NetworksGilles Louppe, Michael Kagan, Kyle Cranmer. 982-991 [doi]
- SchNet: A continuous-filter convolutional neural network for modeling quantum interactionsKristof Schütt, Pieter-Jan Kindermans, Huziel Enoc Sauceda Felix, Stefan Chmiela, Alexandre Tkatchenko, Klaus-Robert Müller. 992-1002 [doi]
- Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance SamplesHaw-Shiuan Chang, Erik G. Learned-Miller, Andrew McCallum. 1003-1013 [doi]
- Differentiable Learning of Submodular FunctionsJosip Djolonga, Andreas Krause 0001. 1014-1024 [doi]
- Inductive Representation Learning on Large GraphsWilliam L. Hamilton, Zhitao Ying, Jure Leskovec. 1025-1035 [doi]
- Subset Selection and Summarization in Sequential DataEhsan Elhamifar, M. Clara De Paolis Kaluza. 1036-1045 [doi]
- Question Asking as Program GenerationAnselm Rothe, Brenden M. Lake, Todd M. Gureckis. 1046-1055 [doi]
- Revisiting Perceptron: Efficient and Label-Optimal Learning of HalfspacesSongbai Yan, Chicheng Zhang. 1056-1066 [doi]
- Gradient Descent Can Take Exponential Time to Escape Saddle PointsSimon S. Du, Chi Jin, Jason D. Lee, Michael I. Jordan, Aarti Singh, Barnabás Póczos. 1067-1077 [doi]
- Union of Intersections (UoI) for Interpretable Data Driven Discovery and PredictionKristofer E. Bouchard, Alejandro F. Bujan, Farbod Roosta-Khorasani, Shashanka Ubaru, Prabhat, Antoine Snijders, Jian-Hua Mao, Edward Chang, Michael W. Mahoney, Sharmodeep Bhattacharya. 1078-1086 [doi]
- One-Shot Imitation LearningYan Duan, Marcin Andrychowicz, Bradly C. Stadie, Jonathan Ho, Jonas Schneider, Ilya Sutskever, Pieter Abbeel, Wojciech Zaremba. 1087-1098 [doi]
- Learning the Morphology of Brain Signals Using Alpha-Stable Convolutional Sparse CodingMainak Jas, Tom Dupré la Tour, Umut Simsekli, Alexandre Gramfort. 1099-1108 [doi]
- Integration Methods and Optimization AlgorithmsDamien Scieur, Vincent Roulet, Francis R. Bach, Alexandre d'Aspremont. 1109-1118 [doi]
- Sharpness, Restart and AccelerationVincent Roulet, Alexandre d'Aspremont. 1119-1129 [doi]
- Learning Koopman Invariant Subspaces for Dynamic Mode DecompositionNaoya Takeishi, Yoshinobu Kawahara, Takehisa Yairi. 1130-1140 [doi]
- Soft-to-Hard Vector Quantization for End-to-End Learning Compressible RepresentationsEirikur Agustsson, Fabian Mentzer, Michael Tschannen, Lukas Cavigelli, Radu Timofte, Luca Benini, Luc J. Van Gool. 1141-1151 [doi]
- Learning spatiotemporal piecewise-geodesic trajectories from longitudinal manifold-valued dataStéphanie Allassonnière, Juliette Chevallier, Stephane Oudard. 1152-1160 [doi]
- Improving Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms and Its ApplicationsQinshi Wang, Wei Chen. 1161-1171 [doi]
- Predictive-State Decoders: Encoding the Future into Recurrent NetworksArun Venkatraman, Nicholas Rhinehart, Wen Sun, Lerrel Pinto, Martial Hebert, Byron Boots, Kris M. Kitani, James Andrew Bagnell. 1172-1183 [doi]
- Optimistic posterior sampling for reinforcement learning: worst-case regret boundsShipra Agrawal, Randy Jia. 1184-1194 [doi]
- Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning resultsAntti Tarvainen, Harri Valpola. 1195-1204 [doi]
- Matching neural paths: transfer from recognition to correspondence searchNikolay Savinov, Lubor Ladicky, Marc Pollefeys. 1205-1214 [doi]
- Linearly constrained Gaussian processesCarl Jidling, Niklas Wahlström, Adrian Wills, Thomas B. Schön. 1215-1224 [doi]
- Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming DataJoel A. Tropp, Alp Yurtsever, Madeleine Udell, Volkan Cevher. 1225-1234 [doi]
- Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial NetsKarol Hausman, Yevgen Chebotar, Stefan Schaal, Gaurav S. Sukhatme, Joseph J. Lim. 1235-1245 [doi]
- Learning to Inpaint for Image CompressionMohammad Haris Baig, Vladlen Koltun, Lorenzo Torresani. 1246-1255 [doi]
- Adaptive Bayesian Sampling with Monte Carlo EMAnirban Roychowdhury, Srinivasan Parthasarathy 0001. 1256-1266 [doi]
- ADMM without a Fixed Penalty Parameter: Faster Convergence with New Adaptive PenalizationYi Xu, Mingrui Liu, Qihang Lin, Tianbao Yang. 1267-1277 [doi]
- Shape and Material from SoundZhoutong Zhang, Qiujia Li, Zhengjia Huang, Jiajun Wu 0001, Josh Tenenbaum, Bill Freeman. 1278-1288 [doi]
- Flexible statistical inference for mechanistic models of neural dynamicsJan-Matthis Lueckmann, Pedro J. Goncalves, Giacomo Bassetto, Kaan Öcal, Marcel Nonnenmacher, Jakob H. Macke. 1289-1299 [doi]
- Online Prediction with Selfish ExpertsTim Roughgarden, Okke Schrijvers. 1300-1310 [doi]
- Tensor BiclusteringSoheil Feizi, Hamid Javadi, David Tse. 1311-1320 [doi]
- DPSCREEN: Dynamic Personalized ScreeningKartik Ahuja, William R. Zame, Mihaela van der Schaar. 1321-1332 [doi]
- Learning Unknown Markov Decision Processes: A Thompson Sampling ApproachYi Ouyang, Mukul Gagrani, Ashutosh Nayyar, Rahul Jain 0002. 1333-1342 [doi]
- Testing and Learning on Distributions with Symmetric Noise InvarianceHo Chung Leon Law, Christopher Yau, Dino Sejdinovic. 1343-1353 [doi]
- A Dirichlet Mixture Model of Hawkes Processes for Event Sequence ClusteringHongteng Xu, Hongyuan Zha. 1354-1363 [doi]
- Deanonymization in the Bitcoin P2P NetworkGiulia C. Fanti, Pramod Viswanath. 1364-1373 [doi]
- Accelerated consensus via Min-Sum SplittingPatrick Rebeschini, Sekhar C. Tatikonda. 1374-1384 [doi]
- Generalized Linear Model Regression under Distance-to-set PenaltiesJason Xu, Eric C. Chi, Kenneth Lange. 1385-1394 [doi]
- Adaptive stimulus selection for optimizing neural population responsesBenjamin R. Cowley, Ryan Williamson, Katerina Clemens, Matthew A. Smith, Byron M. Yu. 1395-1405 [doi]
- Nonbacktracking Bounds on the Influence in Independent Cascade ModelsEmmanuel Abbe, Sanjeev R. Kulkarni, Eun Jee Lee. 1406-1415 [doi]
- Learning with Feature Evolvable StreamsBo-Jian Hou, Lijun Zhang 0005, Zhi-Hua Zhou. 1416-1426 [doi]
- Online Convex Optimization with Stochastic ConstraintsHao Yu, Michael J. Neely, Xiaohan Wei. 1427-1437 [doi]
- Max-Margin Invariant Features from Transformed Unlabelled DataDipan K. Pal, Ashwin A. Kannan, Gautam Arakalgud, Marios Savvides. 1438-1446 [doi]
- Regularized Modal Regression with Applications in Cognitive Impairment PredictionXiaoqian Wang, Hong Chen, Weidong Cai, Dinggang Shen, Heng Huang. 1447-1457 [doi]
- Translation Synchronization via Truncated Least SquaresXiangru Huang, Zhenxiao Liang, Chandrajit Bajaj, Qixing Huang. 1458-1467 [doi]
- From which world is your graphCheng Li, Felix Ming Fai Wong, Zhenming Liu, Varun Kanade. 1468-1478 [doi]
- A New Alternating Direction Method for Linear ProgrammingSinong Wang, Ness B. Shroff. 1479-1487 [doi]
- Regret Analysis for Continuous Dueling BanditWataru Kumagai. 1488-1497 [doi]
- Best Response RegressionOmer Ben-Porat, Moshe Tennenholtz. 1498-1507 [doi]
- TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep LearningWei Wen, Cong Xu, Feng Yan, Chunpeng Wu, Yandan Wang, Yiran Chen, Hai Li. 1508-1518 [doi]
- Learning Affinity via Spatial Propagation NetworksSifei Liu, Shalini De Mello, Jinwei Gu, Guangyu Zhong, Ming-Hsuan Yang 0001, Jan Kautz. 1519-1529 [doi]
- Linear regression without correspondenceDaniel J. Hsu, Kevin Shi, Xiaorui Sun. 1530-1539 [doi]
- NeuralFDR: Learning Discovery Thresholds from Hypothesis FeaturesFei Xia, Martin J. Zhang, James Y. Zou, David Tse. 1540-1549 [doi]
- Cost efficient gradient boostingSven Peter, Ferran Diego, Fred A. Hamprecht, Boaz Nadler. 1550-1560 [doi]
- Probabilistic Rule Realization and SelectionHaizi Yu, Tianxi Li, Lav R. Varshney. 1561-1571 [doi]
- Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite DimensionsAryeh Kontorovich, Sivan Sabato, Roi Weiss. 1572-1582 [doi]
- A Scale Free Algorithm for Stochastic Bandits with Bounded KurtosisTor Lattimore. 1583-1592 [doi]
- Learning Multiple Tasks with Multilinear Relationship NetworksMingsheng Long, Zhangjie Cao, Jianmin Wang, Philip S. Yu. 1593-1602 [doi]
- Deep HyperalignmentMuhammad Yousefnezhad, Daoqiang Zhang. 1603-1611 [doi]
- Online to Offline Conversions, Universality and Adaptive Minibatch SizesKfir Y. Levy. 1612-1621 [doi]
- Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite Sum StructureAlberto Bietti, Julien Mairal. 1622-1632 [doi]
- Deep Learning with Topological SignaturesChristoph Hofer, Roland Kwitt, Marc Niethammer, Andreas Uhl. 1633-1643 [doi]
- Predicting User Activity Level In Point Processes With Mass Transport EquationYichen Wang, Xiaojing Ye, Hongyuan Zha, Le Song. 1644-1654 [doi]
- Submultiplicative Glivenko-Cantelli and Uniform Convergence of RevenuesNoga Alon, Moshe Babaioff, Yannai A. Gonczarowski, Yishay Mansour, Shay Moran, Amir Yehudayoff. 1655-1664 [doi]
- Deep Dynamic Poisson Factorization ModelChengYue Gong, Win-Bin Huang. 1665-1673 [doi]
- Positive-Unlabeled Learning with Non-Negative Risk EstimatorRyuichi Kiryo, Gang Niu, Marthinus Christoffel du Plessis, Masashi Sugiyama. 1674-1684 [doi]
- Optimal Sample Complexity of M-wise Data for Top-K RankingMinje Jang, Sunghyun Kim, Changho Suh, Sewoong Oh. 1685-1695 [doi]
- What-If Reasoning using Counterfactual Gaussian ProcessesPeter Schulam, Suchi Saria. 1696-1706 [doi]
- QSGD: Communication-Efficient SGD via Gradient Quantization and EncodingDan Alistarh, Demjan Grubic, Jerry Li 0001, Ryota Tomioka, Milan Vojnovic. 1707-1718 [doi]
- Convergent Block Coordinate Descent for Training Tikhonov Regularized Deep Neural NetworksZiming Zhang, Matthew Brand. 1719-1728 [doi]
- Train longer, generalize better: closing the generalization gap in large batch training of neural networksElad Hoffer, Itay Hubara, Daniel Soudry. 1729-1739 [doi]
- Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural NetworksUrs Köster, Tristan Webb, Xin Wang, Marcel Nassar, Arjun K. Bansal, William Constable, Oguz Elibol, Stewart Hall, Luke Hornof, Amir Khosrowshahi, Carey Kloss, Ruby J. Pai, Naveen Rao. 1740-1750 [doi]
- Model evidence from nonequilibrium simulationsMichael Habeck. 1751-1760 [doi]
- Minimal Exploration in Structured Stochastic BanditsRichard Combes, Stefan Magureanu, Alexandre Proutière. 1761-1769 [doi]
- Learned D-AMP: Principled Neural Network based Compressive Image RecoveryChristopher A. Metzler, Ali Mousavi, Richard G. Baraniuk. 1770-1781 [doi]
- Deliberation Networks: Sequence Generation Beyond One-Pass DecodingYingce Xia, Fei Tian, Lijun Wu, Jianxin Lin, Tao Qin, Nenghai Yu, Tie-Yan Liu. 1782-1792 [doi]
- Adaptive Clustering through Semidefinite ProgrammingMartin Royer. 1793-1801 [doi]
- Log-normality and Skewness of Estimated State/Action Values in Reinforcement LearningLiangpeng Zhang, Ke Tang, Xin Yao 0001. 1802-1812 [doi]
- Repeated Inverse Reinforcement LearningKareem Amin, Nan Jiang, Satinder P. Singh. 1813-1822 [doi]
- The Numerics of GANsLars M. Mescheder, Sebastian Nowozin, Andreas Geiger. 1823-1833 [doi]
- Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct SearchLuigi Acerbi, Wei Ji. 1834-1844 [doi]
- Learning Chordal Markov Networks via Branch and BoundKari Rantanen, Antti Hyttinen, Matti Järvisalo. 1845-1855 [doi]
- Revenue Optimization with Approximate Bid PredictionsAndres Muñoz Medina, Sergei Vassilvitskii. 1856-1864 [doi]
- Solving Most Systems of Random Quadratic EquationsGang Wang, Georgios B. Giannakis, Yousef Saad, Jie Chen. 1865-1875 [doi]
- Unsupervised Learning of Disentangled and Interpretable Representations from Sequential DataWei-Ning Hsu, Yu Zhang, James R. Glass. 1876-1887 [doi]
- Lookahead Bayesian Optimization with Inequality ConstraintsRémi Lam, Karen Willcox. 1888-1898 [doi]
- Hierarchical Methods of MomentsMatteo Ruffini, Guillaume Rabusseau, Borja Balle. 1899-1908 [doi]
- Interpretable and Globally Optimal Prediction for Textual Grounding using Image ConceptsRaymond Yeh, Jinjun Xiong, Wen-mei W. Hwu, Minh Do, Alexander G. Schwing. 1909-1919 [doi]
- Revisit Fuzzy Neural Network: Demystifying Batch Normalization and ReLU with Generalized Hamming NetworkLixin Fan. 1920-1929 [doi]
- Speeding Up Latent Variable Gaussian Graphical Model Estimation via Nonconvex OptimizationPan Xu, Jian Ma, Quanquan Gu. 1930-1941 [doi]
- Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-Normalized ModelsSergey Ioffe. 1942-1950 [doi]
- Generating steganographic images via adversarial trainingJamie Hayes, George Danezis. 1951-1960 [doi]
- Near-linear time approximation algorithms for optimal transport via Sinkhorn iterationJason Altschuler, Jonathan Weed, Philippe Rigollet. 1961-1971 [doi]
- PixelGAN AutoencodersAlireza Makhzani, Brendan J. Frey. 1972-1982 [doi]
- Consistent Multitask Learning with Nonlinear Output RelationsCarlo Ciliberto, Alessandro Rudi, Lorenzo Rosasco, Massimiliano Pontil. 1983-1993 [doi]
- Alternating minimization for dictionary learning with random initializationNiladri S. Chatterji, Peter L. Bartlett. 1994-2003 [doi]
- Learning ReLUs via Gradient DescentMahdi Soltanolkotabi. 2004-2014 [doi]
- Stabilizing Training of Generative Adversarial Networks through RegularizationKevin Roth, Aurélien Lucchi, Sebastian Nowozin, Thomas Hofmann. 2015-2025 [doi]
- Expectation Propagation with Stochastic Kinetic Model in Complex Interaction SystemsLe Fang, Fan Yang, Wen Dong 0001, Tong Guan, Chunming Qiao. 2026-2036 [doi]
- Data-Efficient Reinforcement Learning in Continuous State-Action Gaussian-POMDPsRowan McAllister, Carl Edward Rasmussen. 2037-2046 [doi]
- Compatible Reward Inverse Reinforcement LearningAlberto Maria Metelli, Matteo Pirotta, Marcello Restelli. 2047-2056 [doi]
- First-Order Adaptive Sample Size Methods to Reduce Complexity of Empirical Risk MinimizationAryan Mokhtari, Alejandro Ribeiro. 2057-2065 [doi]
- Hiding Images in Plain Sight: Deep SteganographyShumeet Baluja. 2066-2076 [doi]
- Neural Program Meta-InductionJacob Devlin, Rudy R. Bunel, Rishabh Singh, Matthew J. Hausknecht, Pushmeet Kohli. 2077-2085 [doi]
- Bayesian Dyadic Trees and Histograms for RegressionStéphanie van der Pas, Veronika Rocková. 2086-2096 [doi]
- A graph-theoretic approach to multitaskingNoga Alon, Daniel Reichman 0001, Igor Shinkar, Tal Wagner, Sebastian Musslick, Jonathan D. Cohen, Tom Griffiths, Biswadip Dey, Kayhan Özcimder. 2097-2106 [doi]
- Consistent Robust RegressionKush Bhatia, Prateek Jain 0002, Parameswaran Kamalaruban, Purushottam Kar. 2107-2116 [doi]
- Natural Value Approximators: Learning when to Trust Past EstimatesZhongwen Xu, Joseph Modayil, Hado P. van Hasselt, André Barreto, David Silver, Tom Schaul. 2117-2125 [doi]
- Bandits Dueling on Partially Ordered SetsJulien Audiffren, Liva Ralaivola. 2126-2135 [doi]
- Elementary Symmetric Polynomials for Optimal Experimental DesignZelda E. Mariet, Suvrit Sra. 2136-2145 [doi]
- Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of SymbolsSerhii Havrylov, Ivan Titov. 2146-2156 [doi]
- Training Deep Networks without Learning Rates Through Coin BettingFrancesco Orabona, Tatiana Tommasi. 2157-2167 [doi]
- Pixels to Graphs by Associative EmbeddingAlejandro Newell, Jia Deng. 2168-2177 [doi]
- Runtime Neural PruningJi Lin, Yongming Rao, Jiwen Lu, Jie Zhou 0001. 2178-2188 [doi]
- Eigenvalue Decay Implies Polynomial-Time Learnability for Neural NetworksSurbhi Goel, Adam R. Klivans. 2189-2199 [doi]
- MMD GAN: Towards Deeper Understanding of Moment Matching NetworkChun-Liang Li, Wei-Cheng Chang, Yu Cheng, Yiming Yang, Barnabás Póczos. 2200-2210 [doi]
- The Reversible Residual Network: Backpropagation Without Storing ActivationsAidan N. Gomez, Mengye Ren, Raquel Urtasun, Roger B. Grosse. 2211-2221 [doi]
- Fast Rates for Bandit Optimization with Upper-Confidence Frank-WolfeQuentin Berthet, Vianney Perchet. 2222-2231 [doi]
- Zap Q-LearningAdithya M. Devraj, Sean R. Meyn. 2232-2241 [doi]
- Expectation Propagation for t-Exponential Family Using q-AlgebraFutoshi Futami, Issei Sato, Masashi Sugiyama. 2242-2251 [doi]
- Few-Shot Learning Through an Information Retrieval LensEleni Triantafillou, Richard S. Zemel, Raquel Urtasun. 2252-2262 [doi]
- Formal Guarantees on the Robustness of a Classifier against Adversarial ManipulationMatthias Hein, Maksym Andriushchenko. 2263-2273 [doi]
- Associative Embedding: End-to-End Learning for Joint Detection and GroupingAlejandro Newell, Zhiao Huang, Jia Deng. 2274-2284 [doi]
- Practical Locally Private Heavy HittersRaef Bassily, Kobbi Nissim, Uri Stemmer, Abhradeep Guha Thakurta. 2285-2293 [doi]
- Large-Scale Quadratically Constrained Quadratic Program via Low-Discrepancy SequencesKinjal Basu, Ankan Saha, Shaunak Chatterjee. 2294-2304 [doi]
- Inhomogeneous Hypergraph Clustering with ApplicationsPan Li, Olgica Milenkovic. 2305-2315 [doi]
- Differentiable Learning of Logical Rules for Knowledge Base ReasoningFan Yang, Zhilin Yang, William W. Cohen. 2316-2325 [doi]
- Deep Multi-task Gaussian Processes for Survival Analysis with Competing Risks2326-2334 [doi]
- Masked Autoregressive Flow for Density EstimationGeorge Papamakarios, Iain Murray, Theo Pavlakou. 2335-2344 [doi]
- Non-convex Finite-Sum Optimization Via SCSG MethodsLihua Lei, Cheng Ju, Jianbo Chen, Michael I. Jordan. 2345-2355 [doi]
- Beyond normality: Learning sparse probabilistic graphical models in the non-Gaussian settingRebecca Morrison, Ricardo Baptista, Youssef Marzouk. 2356-2366 [doi]
- An inner-loop free solution to inverse problems using deep neural networksKai Fan, Qi Wei, Lawrence Carin, Katherine A. Heller. 2367-2377 [doi]
- OnACID: Online Analysis of Calcium Imaging Data in Real TimeAndrea Giovannucci, Johannes Friedrich, Matt Kaufman, Anne Churchland, Dmitri Chklovskii, Liam Paninski, Eftychios A. Pnevmatikakis. 2378-2388 [doi]
- Collaborative PAC LearningAvrim Blum, Nika Haghtalab, Ariel D. Procaccia, Mingda Qiao. 2389-2398 [doi]
- Fast Black-box Variational Inference through Stochastic Trust-Region OptimizationJeffrey Regier, Michael I. Jordan, Jon McAuliffe. 2399-2408 [doi]
- Scalable Demand-Aware RecommendationJinfeng Yi, Cho-Jui Hsieh, Kush R. Varshney, Lijun Zhang 0005, Yao Li. 2409-2418 [doi]
- SGD Learns the Conjugate Kernel Class of the NetworkAmit Daniely. 2419-2427 [doi]
- Noise-Tolerant Interactive Learning Using Pairwise ComparisonsYichong Xu, Hongyang Zhang, Aarti Singh, Artur Dubrawski, Kyle Miller. 2428-2437 [doi]
- Analyzing Hidden Representations in End-to-End Automatic Speech Recognition SystemsYonatan Belinkov, James Glass. 2438-2448 [doi]
- Generative Local Metric Learning for Kernel RegressionYung-Kyun Noh, Masashi Sugiyama, Kee-Eung Kim, Frank C. Park, Daniel D. Lee. 2449-2459 [doi]
- Information Theoretic Properties of Markov Random Fields, and their Algorithmic ApplicationsLinus Hamilton, Frederic Koehler, Ankur Moitra. 2460-2469 [doi]
- Fitting Low-Rank Tensors in Constant TimeKohei Hayashi, Yuichi Yoshida. 2470-2478 [doi]
- Deep Supervised Discrete HashingQi Li, Zhenan Sun, Ran He, Tieniu Tan. 2479-2488 [doi]
- Using Options and Covariance Testing for Long Horizon Off-Policy Policy EvaluationZhaohan Guo, Philip S. Thomas, Emma Brunskill. 2489-2498 [doi]
- How regularization affects the critical points in linear networksAmirhossein Taghvaei, Jin W. Kim, Prashant G. Mehta. 2499-2509 [doi]
- Fisher GANYoussef Mroueh, Tom Sercu. 2510-2520 [doi]
- Information-theoretic analysis of generalization capability of learning algorithmsAolin Xu, Maxim Raginsky. 2521-2530 [doi]
- Sparse Approximate Conic HullsGreg Van Buskirk, Ben Raichel, Nicholas Ruozzi. 2531-2541 [doi]
- Rigorous Dynamics and Consistent Estimation in Arbitrarily Conditioned Linear SystemsAlyson K. Fletcher, Mojtaba Sahraee-Ardakan, Sundeep Rangan, Philip Schniter. 2542-2551 [doi]
- Toward Goal-Driven Neural Network Models for the Rodent Whisker-Trigeminal SystemChengxu Zhuang, Jonas Kubilius, Mitra J. Z. Hartmann, Daniel L. Yamins. 2552-2562 [doi]
- Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERMKatrina Ligett, Seth Neel, Aaron Roth, Bo Waggoner, Steven Z. Wu. 2563-2573 [doi]
- EX2: Exploration with Exemplar Models for Deep Reinforcement LearningJustin Fu, John D. Co-Reyes, Sergey Levine. 2574-2584 [doi]
- Multitask Spectral Learning of Weighted AutomataGuillaume Rabusseau, Borja Balle, Joelle Pineau. 2585-2594 [doi]
- Multi-way Interacting Regression via Factorization MachinesMikhail Yurochkin, XuanLong Nguyen, Nikolaos Vasiloglou. 2595-2603 [doi]
- Predicting Organic Reaction Outcomes with Weisfeiler-Lehman NetworkWengong Jin, Connor W. Coley, Regina Barzilay, Tommi S. Jaakkola. 2604-2613 [doi]
- Practical Data-Dependent Metric Compression with Provable GuaranteesPiotr Indyk, Ilya P. Razenshteyn, Tal Wagner. 2614-2623 [doi]
- REBAR: Low-variance, unbiased gradient estimates for discrete latent variable modelsGeorge Tucker, Andriy Mnih, Chris J. Maddison, John Lawson, Jascha Sohl-Dickstein. 2624-2633 [doi]
- Nonlinear random matrix theory for deep learningJeffrey Pennington, Pratik Worah. 2634-2643 [doi]
- Parallel Streaming Wasserstein BarycentersMatthew Staib, Sebastian Claici, Justin M. Solomon, Stefanie Jegelka. 2644-2655 [doi]
- ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy GamesYuandong Tian, Qucheng Gong, Wenling Shang, Yuxin Wu, C. Lawrence Zitnick. 2656-2666 [doi]
- Dual Discriminator Generative Adversarial NetsTu Nguyen, Trung Le, Hung Vu, Dinh Q. Phung. 2667-2677 [doi]
- Dynamic Revenue SharingSantiago R. Balseiro, Max Lin, Vahab S. Mirrokni, Renato Paes Leme, Song Zuo. 2678-2686 [doi]
- Decomposition-Invariant Conditional Gradient for General Polytopes with Line SearchMohammad Ali Bashiri, Xinhua Zhang. 2687-2697 [doi]
- VAIN: Attentional Multi-agent Predictive ModelingYedid Hoshen. 2698-2708 [doi]
- An Empirical Bayes Approach to Optimizing Machine Learning AlgorithmsJames McInerney. 2709-2718 [doi]
- Differentially Private Empirical Risk Minimization Revisited: Faster and More GeneralDi Wang, Minwei Ye, Jinhui Xu. 2719-2728 [doi]
- Variational Inference via \chi Upper Bound MinimizationAdji Bousso Dieng, Dustin Tran, Rajesh Ranganath, John William Paisley, David M. Blei. 2729-2738 [doi]
- On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse LearningXingguo Li, Lin Yang, Jason Ge, Jarvis D. Haupt, Tong Zhang, Tuo Zhao. 2739-2749 [doi]
- #Exploration: A Study of Count-Based Exploration for Deep Reinforcement LearningHaoran Tang, Rein Houthooft, Davis Foote, Adam Stooke, Xi Chen, Yan Duan, John Schulman, Filip De Turck, Pieter Abbeel. 2750-2759 [doi]
- An Empirical Study on The Properties of Random Bases for Kernel MethodsMaximilian Alber, Pieter-Jan Kindermans, Kristof Schütt, Klaus-Robert Müller, Fei Sha. 2760-2771 [doi]
- Bridging the Gap Between Value and Policy Based Reinforcement LearningOfir Nachum, Mohammad Norouzi, Kelvin Xu, Dale Schuurmans. 2772-2782 [doi]
- Premise Selection for Theorem Proving by Deep Graph EmbeddingMingzhe Wang, Yihe Tang, Jian Wang, Jia Deng. 2783-2793 [doi]
- A Bayesian Data Augmentation Approach for Learning Deep ModelsToan Tran, Trung Pham, Gustavo Carneiro, Lyle J. Palmer, Ian D. Reid 0001. 2794-2803 [doi]
- Principles of Riemannian Geometry in Neural NetworksMichael Hauser, Asok Ray. 2804-2813 [doi]
- Cold-Start Reinforcement Learning with Softmax Policy GradientNan Ding, Radu Soricut. 2814-2823 [doi]
- Online Dynamic ProgrammingHolakou Rahmanian, Manfred K. Warmuth. 2824-2834 [doi]
- Alternating Estimation for Structured High-Dimensional Multi-Response ModelsSheng Chen, Arindam Banerjee. 2835-2844 [doi]
- Convolutional Gaussian ProcessesMark van der Wilk, Carl Edward Rasmussen, James Hensman. 2845-2854 [doi]
- Estimation of the covariance structure of heavy-tailed distributionsXiaohan Wei, Stanislav Minsker. 2855-2864 [doi]
- Mean Field Residual Networks: On the Edge of ChaosGe Yang, Samuel Schoenholz. 2865-2873 [doi]
- Decomposable Submodular Function Minimization: Discrete and ContinuousAlina Ene, Huy L. Nguyen, László A. Végh. 2874-2884 [doi]
- Gauging Variational InferenceSungsoo Ahn, Michael Chertkov, Jinwoo Shin. 2885-2894 [doi]
- Deep Recurrent Neural Network-Based Identification of Precursor microRNAsSeunghyun Park, Seonwoo Min, Hyun Soo Choi, Sungroh Yoon. 2895-2904 [doi]
- Robust Estimation of Neural Signals in Calcium ImagingHakan Inan, Murat A. Erdogdu, Mark J. Schnitzer. 2905-2914 [doi]
- State Aware Imitation LearningYannick Schroecker, Charles L. Isbell. 2915-2924 [doi]
- Beyond Parity: Fairness Objectives for Collaborative FilteringSirui Yao, Bert Huang. 2925-2934 [doi]
- A PAC-Bayesian Analysis of Randomized Learning with Application to Stochastic Gradient DescentBen London. 2935-2944 [doi]
- Fully Decentralized Policies for Multi-Agent Systems: An Information Theoretic ApproachRoel Dobbe, David Fridovich-Keil, Claire Tomlin. 2945-2954 [doi]
- Model-Powered Conditional Independence TestRajat Sen, Ananda Theertha Suresh, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai. 2955-2965 [doi]
- Deep Voice 2: Multi-Speaker Neural Text-to-SpeechAndrew Gibiansky, Sercan Ömer Arik, Gregory Frederick Diamos, John Miller, Kainan Peng, Wei Ping, Jonathan Raiman, Yanqi Zhou. 2966-2974 [doi]
- Variance-based Regularization with Convex ObjectivesHongseok Namkoong, John C. Duchi. 2975-2984 [doi]
- Deep Lattice Networks and Partial Monotonic FunctionsSeungil You, David Ding, Kevin Robert Canini, Jan Pfeifer, Maya R. Gupta. 2985-2993 [doi]
- Continual Learning with Deep Generative ReplayHanul Shin, Jung Kwon Lee, Jaehong Kim, Jiwon Kim. 2994-3003 [doi]
- AIDE: An algorithm for measuring the accuracy of probabilistic inference algorithmsMarco F. Cusumano-Towner, Vikash K. Mansinghka. 3004-3014 [doi]
- Learning Causal Structures Using Regression InvarianceAmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Kun Zhang. 3015-3025 [doi]
- Online Influence Maximization under Independent Cascade Model with Semi-Bandit FeedbackZheng Wen, Branislav Kveton, Michal Valko, Sharan Vaswani. 3026-3036 [doi]
- Near Minimax Optimal Players for the Finite-Time 3-Expert Prediction ProblemYasin Abbasi-Yadkori, Peter L. Bartlett, Victor Gabillon. 3037-3045 [doi]
- Reinforcement Learning under Model MismatchAurko Roy, Huan Xu, Sebastian Pokutta. 3046-3055 [doi]
- Hierarchical Attentive Recurrent TrackingAdam R. Kosiorek, Alex Bewley, Ingmar Posner. 3056-3064 [doi]
- Tomography of the London Underground: a Scalable Model for Origin-Destination DataNicolò Colombo, Ricardo Silva, Soong Moon Kang. 3065-3076 [doi]
- Rotting BanditsNir Levine, Koby Crammer, Shie Mannor. 3077-3086 [doi]
- Unbiased estimates for linear regression via volume samplingMichal Derezinski, Manfred K. Warmuth. 3087-3096 [doi]
- Approximation Bounds for Hierarchical Clustering: Average Linkage, Bisecting K-means, and Local SearchBenjamin Moseley, Joshua Wang. 3097-3106 [doi]
- Adaptive Accelerated Gradient Converging Method under H\"{o}lderian Error Bound ConditionMingrui Liu, Tianbao Yang. 3107-3117 [doi]
- Stein Variational Gradient Descent as Gradient FlowQiang Liu. 3118-3126 [doi]
- Partial Hard Thresholding: Towards A Principled Analysis of Support RecoveryJie Shen, Ping Li. 3127-3137 [doi]
- Shallow Updates for Deep Reinforcement LearningNir Levine, Tom Zahavy, Daniel J. Mankowitz, Aviv Tamar, Shie Mannor. 3138-3148 [doi]
- LightGBM: A Highly Efficient Gradient Boosting Decision TreeGuolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, Tie-Yan Liu. 3149-3157 [doi]
- Adversarial Ranking for Language GenerationKevin Lin, Dianqi Li, Xiaodong He, Ming-Ting Sun, Zhengyou Zhang. 3158-3168 [doi]
- Regret Minimization in MDPs with Options without Prior KnowledgeRonan Fruit, Matteo Pirotta, Alessandro Lazaric, Emma Brunskill. 3169-3179 [doi]
- Net-Trim: Convex Pruning of Deep Neural Networks with Performance GuaranteeAlireza Aghasi, Afshin Abdi, Nam Nguyen, Justin Romberg. 3180-3189 [doi]
- Graph Matching via Multiplicative Update AlgorithmBo Jiang, Jin Tang, Chris Ding, Yihong Gong, Bin Luo. 3190-3198 [doi]
- Dynamic Importance Sampling for Anytime Bounds of the Partition FunctionQi Lou, Rina Dechter, Alexander T. Ihler. 3199-3207 [doi]
- Is the Bellman residual a bad proxy?Matthieu Geist, Bilal Piot, Olivier Pietquin. 3208-3217 [doi]
- Generalization Properties of Learning with Random FeaturesAlessandro Rudi, Lorenzo Rosasco. 3218-3228 [doi]
- Differentially private Bayesian learning on distributed dataMikko Heikkilä, Eemil Lagerspetz, Samuel Kaski, Kana Shimizu, Sasu Tarkoma, Antti Honkela. 3229-3238 [doi]
- Learning to Compose Domain-Specific Transformations for Data AugmentationAlexander J. Ratner, Henry R. Ehrenberg, Zeshan Hussain, Jared Dunnmon, Christopher Ré. 3239-3249 [doi]
- Wasserstein Learning of Deep Generative Point Process ModelsShuai Xiao, Mehrdad Farajtabar, Xiaojing Ye, Junchi Yan, Xiaokang Yang, Le Song, Hongyuan Zha. 3250-3259 [doi]
- Ensemble SamplingXiuyuan Lu, Benjamin Van Roy. 3260-3268 [doi]
- Language Modeling with Recurrent Highway HypernetworksJoseph Suarez. 3269-3278 [doi]
- Adaptive SVRG Methods under Error Bound Conditions with Unknown Growth ParameterYi Xu, Qihang Lin, Tianbao Yang. 3279-3289 [doi]
- Bayesian Compression for Deep LearningChristos Louizos, Karen Ullrich, Max Welling. 3290-3300 [doi]
- Streaming Sparse Gaussian Process ApproximationsThang D. Bui, Cuong V. Nguyen, Richard E. Turner. 3301-3309 [doi]
- VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational LearningAkash Srivastava, Lazar Valkoz, Chris Russell, Michael U. Gutmann, Charles A. Sutton. 3310-3320 [doi]
- Sparse Embedded k-Means ClusteringWeiwei Liu, Xiao-Bo Shen, Ivor W. Tsang. 3321-3329 [doi]
- Dynamic-Depth Context Tree WeightingJoão V. Messias, Shimon Whiteson. 3330-3339 [doi]
- A Regularized Framework for Sparse and Structured Neural AttentionVlad Niculae, Mathieu Blondel. 3340-3350 [doi]
- Multi-output Polynomial Networks and Factorization MachinesMathieu Blondel, Vlad Niculae, Takuma Otsuka, Naonori Ueda. 3351-3361 [doi]
- Clustering Billions of Reads for DNA Data StorageCyrus Rashtchian, Konstantin Makarychev, Miklós Z. Rácz, Siena Ang, Djordje Jevdjic, Sergey Yekhanin, Luis Ceze, Karin Strauss. 3362-3373 [doi]
- Multi-Objective Non-parametric Sequential PredictionGuy Uziel, Ran El-Yaniv. 3374-3383 [doi]
- A Universal Analysis of Large-Scale Regularized Least Squares SolutionsAshkan Panahi, Babak Hassibi. 3384-3393 [doi]
- Deep SetsManzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabás Póczos, Ruslan R. Salakhutdinov, Alexander J. Smola. 3394-3404 [doi]
- ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather eventsEvan Racah, Christopher Beckham, Tegan Maharaj, Samira Ebrahimi Kahou, Prabhat, Chris Pal. 3405-3416 [doi]
- Process-constrained batch Bayesian optimisationPratibha Vellanki, Santu Rana, Sunil Kumar Gupta 0001, David Rubin, Alessandra Sutti, Thomas Dorin, Murray Height, Paul G. Sanders, Svetha Venkatesh. 3417-3426 [doi]
- Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes3427-3435 [doi]
- Spherical convolutions and their application in molecular modellingWouter Boomsma, Jes Frellsen. 3436-3446 [doi]
- Efficient Optimization for Linear Dynamical Systems with Applications to Clustering and Sparse CodingWen-bing Huang, Mehrtash Harandi, Tong Zhang 0001, Lijie Fan, Fuchun Sun, JunZhou Huang. 3447-3457 [doi]
- On Optimal Generalizability in Parametric LearningAhmad Beirami, Meisam Razaviyayn, Shahin Shahrampour, Vahid Tarokh. 3458-3468 [doi]
- Near Optimal Sketching of Low-Rank Tensor RegressionXingguo Li, Jarvis D. Haupt, David P. Woodruff. 3469-3479 [doi]
- Tractability in Structured Probability SpacesArthur Choi, Yujia Shen, Adnan Darwiche. 3480-3488 [doi]
- Model-based Bayesian inference of neural activity and connectivity from all-optical interrogation of a neural circuitLaurence Aitchison, Lloyd Russell, Adam M. Packer, Jinyao Yan, Philippe Castonguay, Michael Häusser, Srinivas C. Turaga. 3489-3498 [doi]
- Gaussian process based nonlinear latent structure discovery in multivariate spike train dataAnqi Wu, Nicholas G. Roy, Stephen Keeley, Jonathan W. Pillow. 3499-3508 [doi]
- Neural system identification for large populations separating "what" and "where"David Klindt, Alexander S. Ecker, Thomas Euler, Matthias Bethge. 3509-3519 [doi]
- Certified Defenses for Data Poisoning AttacksJacob Steinhardt, Pang Wei Koh, Percy S. Liang. 3520-3532 [doi]
- Eigen-Distortions of Hierarchical RepresentationsAlexander Berardino, Valero Laparra, Johannes Ballé, Eero P. Simoncelli. 3533-3542 [doi]
- Limitations on Variance-Reduction and Acceleration Schemes for Finite Sums OptimizationYossi Arjevani. 3543-3552 [doi]
- Unsupervised Sequence Classification using Sequential Output StatisticsYu Liu, Jianshu Chen, Li Deng. 3553-3562 [doi]
- Subset Selection under NoiseChao Qian, Jing-Cheng Shi, Yang Yu 0001, Ke Tang, Zhi-Hua Zhou. 3563-3573 [doi]
- Collecting Telemetry Data PrivatelyBolin Ding, Janardhan Kulkarni, Sergey Yekhanin. 3574-3583 [doi]
- Concrete DropoutYarin Gal, Jiri Hron, Alex Kendall. 3584-3593 [doi]
- Adaptive Batch Size for Safe Policy GradientsMatteo Papini, Matteo Pirotta, Marcello Restelli. 3594-3603 [doi]
- A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised LearningMarco Fraccaro, Simon Kamronn, Ulrich Paquet, Ole Winther. 3604-3613 [doi]
- PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inferenceJonathan H. Huggins, Ryan P. Adams, Tamara Broderick. 3614-3624 [doi]
- Bayesian GANYunus Saatci, Andrew Wilson. 3625-3634 [doi]
- Off-policy evaluation for slate recommendationAdith Swaminathan, Akshay Krishnamurthy, Alekh Agarwal, Miroslav Dudík, John Langford, Damien Jose, Imed Zitouni. 3635-3645 [doi]
- A multi-agent reinforcement learning model of common-pool resource appropriationJulien Pérolat, Joel Z. Leibo, Vinícius Flores Zambaldi, Charles Beattie, Karl Tuyls, Thore Graepel. 3646-3655 [doi]
- On the Optimization Landscape of Tensor DecompositionsRong Ge 0001, Tengyu Ma. 3656-3666 [doi]
- High-Order Attention Models for Visual Question AnsweringIdan Schwartz, Alexander G. Schwing, Tamir Hazan. 3667-3677 [doi]
- Sparse convolutional coding for neuronal assembly detectionSven Peter, Elke Kirschbaum, Martin Both, Lee Campbell, Brandon Harvey, Conor Heins, Daniel Durstewitz, Ferran Diego, Fred A. Hamprecht. 3678-3688 [doi]
- Quantifying how much sensory information in a neural code is relevant for behaviorGiuseppe Pica, Eugenio Piasini, Houman Safaai, Caroline Runyan, Christopher Harvey, Mathew E. Diamond, Christoph Kayser, Tommaso Fellin, Stefano Panzeri. 3689-3699 [doi]
- Geometric Matrix Completion with Recurrent Multi-Graph Neural NetworksFederico Monti, Michael M. Bronstein, Xavier Bresson. 3700-3710 [doi]
- Reducing Reparameterization Gradient VarianceAndrew C. Miller, Nick Foti, Alexander D'Amour, Ryan P. Adams. 3711-3721 [doi]
- Visual Reference Resolution using Attention Memory for Visual DialogPaul Hongsuck Seo, Andreas Lehrmann, Bohyung Han, Leonid Sigal. 3722-3732 [doi]
- Joint distribution optimal transportation for domain adaptationNicolas Courty, Rémi Flamary, Amaury Habrard, Alain Rakotomamonjy. 3733-3742 [doi]
- Multiresolution Kernel Approximation for Gaussian Process RegressionYi Ding, Risi Kondor, Jonathan Eskreis-Winkler. 3743-3751 [doi]
- Collapsed variational Bayes for Markov jump processesBoqian Zhang, Jiangwei Pan, Vinayak A. Rao. 3752-3760 [doi]
- Universal consistency and minimax rates for online Mondrian ForestsJaouad Mourtada, Stéphane Gaïffas, Erwan Scornet. 3761-3770 [doi]
- Welfare Guarantees from DataDarrell Hoy, Denis Nekipelov, Vasilis Syrgkanis. 3771-3780 [doi]
- Diving into the shallows: a computational perspective on large-scale shallow learningSiyuan Ma, Mikhail Belkin. 3781-3790 [doi]
- End-to-end Differentiable ProvingTim Rocktäschel, Sebastian Riedel 0001. 3791-3803 [doi]
- Influence Maximization with ε-Almost Submodular Threshold FunctionsQiang Li, Wei Chen, Xiaoming Sun, Jialin Zhang. 3804-3814 [doi]
- InfoGAIL: Interpretable Imitation Learning from Visual DemonstrationsYunzhu Li, Jiaming Song, Stefano Ermon. 3815-3825 [doi]
- Variational Laws of Visual Attention for Dynamic ScenesDario Zanca, Marco Gori. 3826-3835 [doi]
- Recursive Sampling for the Nystrom MethodCameron Musco, Christopher Musco. 3836-3848 [doi]
- Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement LearningShixiang Gu, Tim Lillicrap, Richard E. Turner, Zoubin Ghahramani, Bernhard Schölkopf, Sergey Levine. 3849-3858 [doi]
- Dynamic Routing Between CapsulesSara Sabour, Nicholas Frosst, Geoffrey E. Hinton. 3859-3869 [doi]
- Incorporating Side Information by Adaptive ConvolutionDi Kang, Debarun Dhar, Antoni B. Chan. 3870-3880 [doi]
- Conic Scan-and-Cover algorithms for nonparametric topic modelingMikhail Yurochkin, Aritra Guha, XuanLong Nguyen. 3881-3890 [doi]
- FALKON: An Optimal Large Scale Kernel MethodAlessandro Rudi, Luigi Carratino, Lorenzo Rosasco. 3891-3901 [doi]
- Structured Generative Adversarial NetworksZhijie Deng, Hao Zhang, Xiaodan Liang, Luona Yang, Shizhen Xu, Jun Zhu, Eric P. Xing. 3902-3912 [doi]
- Conservative Contextual Linear BanditsAbbas Kazerouni, Mohammad Ghavamzadeh, Yasin Abbasi, Benjamin Van Roy. 3913-3922 [doi]
- Variational Memory Addressing in Generative ModelsJörg Bornschein, Andriy Mnih, Daniel Zoran, Danilo Jimenez Rezende. 3923-3932 [doi]
- On Tensor Train Rank Minimization : Statistical Efficiency and Scalable AlgorithmMasaaki Imaizumi, Takanori Maehara, Kohei Hayashi. 3933-3942 [doi]
- Scalable Levy Process Priors for Spectral Kernel LearningPhillip A. Jang, Andrew Loeb, Matthew Davidow, Andrew Wilson. 3943-3952 [doi]
- Deep Hyperspherical LearningWeiyang Liu, Yan-Ming Zhang, Xingguo Li, Zhen Liu, Bo Dai, Tuo Zhao, Le Song. 3953-3963 [doi]
- Learning Deep Structured Multi-Scale Features using Attention-Gated CRFs for Contour PredictionDan Xu, Wanli Ouyang, Xavier Alameda-Pineda, Elisa Ricci, Xiaogang Wang, Nicu Sebe. 3964-3973 [doi]
- On-the-fly Operation Batching in Dynamic Computation GraphsGraham Neubig, Yoav Goldberg, Chris Dyer. 3974-3984 [doi]
- Nonlinear Acceleration of Stochastic AlgorithmsDamien Scieur, Francis R. Bach, Alexandre d'Aspremont. 3985-3994 [doi]
- Optimized Pre-Processing for Discrimination PreventionFlávio du Pin Calmon, Dennis Wei, Bhanukiran Vinzamuri, Karthikeyan Natesan Ramamurthy, Kush R. Varshney. 3995-4004 [doi]
- YASS: Yet Another Spike SorterJin Hyung Lee, David E. Carlson, Hooshmand Shokri Razaghi, Weichi Yao, Georges A. Goetz, Espen Hagen, Eleanor Batty, E. J. Chichilnisky, Gaute T. Einevoll, Liam Paninski. 4005-4015 [doi]
- Independence clustering (without a matrix)Daniil Ryabko. 4016-4026 [doi]
- Fast amortized inference of neural activity from calcium imaging data with variational autoencodersArtur Speiser, Jinyao Yan, Evan W. Archer, Lars Buesing, Srinivas C. Turaga, Jakob H. Macke. 4027-4037 [doi]
- Adaptive Active Hypothesis Testing under Limited InformationFabio Cecchi, Nidhi Hegde. 4038-4046 [doi]
- Streaming Weak Submodularity: Interpreting Neural Networks on the FlyEthan Elenberg, Alexandros G. Dimakis, Moran Feldman, Amin Karbasi. 4047-4057 [doi]
- Successor Features for Transfer in Reinforcement LearningAndré Barreto, Will Dabney, Rémi Munos, Jonathan J. Hunt, Tom Schaul, David Silver, Hado P. van Hasselt. 4058-4068 [doi]
- Counterfactual FairnessMatt J. Kusner, Joshua R. Loftus, Chris Russell, Ricardo Silva. 4069-4079 [doi]
- Prototypical Networks for Few-shot LearningJake Snell, Kevin Swersky, Richard S. Zemel. 4080-4090 [doi]
- Triple Generative Adversarial NetsChongxuan Li, Taufik Xu, Jun Zhu, Bo Zhang. 4091-4101 [doi]
- Efficient Sublinear-Regret Algorithms for Online Sparse Linear Regression with Limited ObservationShinji Ito, Daisuke Hatano, Hanna Sumita, Akihiro Yabe, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi. 4102-4111 [doi]
- Mapping distinct timescales of functional interactions among brain networksMali Sundaresan, Arshed Nabeel, Devarajan Sridharan. 4112-4121 [doi]
- Multi-Armed Bandits with Metric Movement CostsTomer Koren, Roi Livni, Yishay Mansour. 4122-4131 [doi]
- Learning A Structured Optimal Bipartite Graph for Co-ClusteringFeiping Nie, Xiaoqian Wang, Cheng Deng, Heng Huang. 4132-4141 [doi]
- Learning Low-Dimensional MetricsBlake Mason, Lalit Jain, Robert D. Nowak. 4142-4150 [doi]
- The Marginal Value of Adaptive Gradient Methods in Machine LearningAshia C. Wilson, Rebecca Roelofs, Mitchell Stern, Nati Srebro, Benjamin Recht. 4151-4161 [doi]
- Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text ClassificationBikash Joshi, Massih-Reza Amini, Ioannis Partalas, Franck Iutzeler, Yury Maximov. 4162-4171 [doi]
- Deconvolutional Paragraph Representation LearningYizhe Zhang, Dinghan Shen, Guoyin Wang, Zhe Gan, Ricardo Henao, Lawrence Carin. 4172-4182 [doi]
- Random Permutation Online Isotonic RegressionWojciech Kotlowski, Wouter M. Koolen, Alan Malek. 4183-4192 [doi]
- A Unified Game-Theoretic Approach to Multiagent Reinforcement LearningMarc Lanctot, Vinícius Flores Zambaldi, Audrunas Gruslys, Angeliki Lazaridou, Karl Tuyls, Julien Pérolat, David Silver, Thore Graepel. 4193-4206 [doi]
- Inverse Filtering for Hidden Markov ModelsRobert Mattila, Cristian R. Rojas, Vikram Krishnamurthy, Bo Wahlberg. 4207-4216 [doi]
- Non-parametric Structured Output NetworksAndreas Lehrmann, Leonid Sigal. 4217-4227 [doi]
- Learning Active Learning from DataKsenia Konyushkova, Raphael Sznitman, Pascal Fua. 4228-4238 [doi]
- VAE Learning via Stein Variational Gradient DescentYunchen Pu, Zhe Gan, Ricardo Henao, Chunyuan Li, Shaobo Han, Lawrence Carin. 4239-4248 [doi]
- Reconstructing perceived faces from brain activations with deep adversarial neural decodingYagmur Güçlütürk, Umut Güçlü, Katja Seeliger, Sander Bosch, Rob van Lier, Marcel A. J. van Gerven. 4249-4260 [doi]
- Efficient Use of Limited-Memory Accelerators for Linear Learning on Heterogeneous SystemsCelestine Dünner, Thomas P. Parnell, Martin Jaggi. 4261-4270 [doi]
- Temporal Coherency based Criteria for Predicting Video Frames using Deep Multi-stage Generative Adversarial NetworksPrateep Bhattacharjee, Sukhendu Das. 4271-4280 [doi]
- Sobolev Training for Neural NetworksWojciech M. Czarnecki, Simon Osindero, Max Jaderberg, Grzegorz Swirszcz, Razvan Pascanu. 4281-4290 [doi]
- Multi-Information Source OptimizationMatthias Poloczek, Jialei Wang, Peter I. Frazier. 4291-4301 [doi]
- Deep Reinforcement Learning from Human PreferencesPaul F. Christiano, Jan Leike, Tom Brown, Miljan Martic, Shane Legg, Dario Amodei. 4302-4310 [doi]
- On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural NetworksArturs Backurs, Piotr Indyk, Ludwig Schmidt. 4311-4321 [doi]
- Policy Gradient With Value Function Approximation For Collective Multiagent PlanningDuc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau. 4322-4332 [doi]
- Adversarial Symmetric Variational AutoencoderYunchen Pu, Weiyao Wang, Ricardo Henao, Liqun Chen, Zhe Gan, Chunyuan Li, Lawrence Carin. 4333-4342 [doi]
- Unified representation of tractography and diffusion-weighted MRI data using sparse multidimensional arraysCesar F. Caiafa, Olaf Sporns, Andrew J. Saykin, Franco Pestilli. 4343-4354 [doi]
- A Minimax Optimal Algorithm for CrowdsourcingThomas Bonald, Richard Combes. 4355-4363 [doi]
- Estimating Accuracy from Unlabeled Data: A Probabilistic Logic ApproachEmmanouil Antonios Platanios, Hoifung Poon, Tom M. Mitchell, Eric Joel Horvitz. 4364-4373 [doi]
- A Decomposition of Forecast Error in Prediction MarketsMiroslav Dudík, Sébastien Lahaie, Ryan M. Rogers, Jennifer Wortman Vaughan. 4374-4383 [doi]
- Safe Adaptive Importance SamplingSebastian U. Stich, Anant Raj, Martin Jaggi. 4384-4394 [doi]
- Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent NetAnirudh Goyal, Nan Rosemary Ke, Surya Ganguli, Yoshua Bengio. 4395-4405 [doi]
- Polynomial Codes: an Optimal Design for High-Dimensional Coded Matrix MultiplicationQian Yu, Mohammad Ali Maddah-Ali, Salman Avestimehr. 4406-4416 [doi]
- Unsupervised Learning of Disentangled Representations from VideoEmily L. Denton, Vighnesh Birodkar. 4417-4426 [doi]
- Federated Multi-Task LearningVirginia Smith, Chao-Kai Chiang, Maziar Sanjabi, Ameet S. Talwalkar. 4427-4437 [doi]
- Is Input Sparsity Time Possible for Kernel Low-Rank Approximation?Cameron Musco, David P. Woodruff. 4438-4448 [doi]
- The Expxorcist: Nonparametric Graphical Models Via Conditional Exponential DensitiesArun Sai Suggala, Mladen Kolar, Pradeep Ravikumar. 4449-4459 [doi]
- Improved Graph Laplacian via Geometric Self-ConsistencyDominique Joncas, Marina Meila, James McQueen. 4460-4469 [doi]
- Dual Path NetworksYunpeng Chen, Jianan Li, Huaxin Xiao, Xiaojie Jin, Shuicheng Yan, Jiashi Feng. 4470-4478 [doi]
- Faster and Non-ergodic O(1/K) Stochastic Alternating Direction Method of MultipliersCong Fang, Feng Cheng, Zhouchen Lin. 4479-4488 [doi]
- A Probabilistic Framework for Nonlinearities in Stochastic Neural NetworksQinliang Su, Xuejun Liao, Lawrence Carin. 4489-4498 [doi]
- Distral: Robust multitask reinforcement learningYee Whye Teh, Victor Bapst, Wojciech M. Czarnecki, John Quan, James Kirkpatrick, Raia Hadsell, Nicolas Heess, Razvan Pascanu. 4499-4509 [doi]
- Online Learning of Optimal Bidding Strategy in Repeated Multi-Commodity AuctionsM. Sevi Baltaoglu, Lang Tong, Qing Zhao. 4510-4520 [doi]
- Trimmed Density Ratio EstimationSong Liu, Akiko Takeda, Taiji Suzuki, Kenji Fukumizu. 4521-4531 [doi]
- Training recurrent networks to generate hypotheses about how the brain solves hard navigation problemsIngmar Kanitscheider, Ila Fiete. 4532-4541 [doi]
- Visual Interaction Networks: Learning a Physics Simulator from VideoNicholas Watters, Daniel Zoran, Theophane Weber, Peter Battaglia, Razvan Pascanu, Andrea Tacchetti. 4542-4550 [doi]
- Reconstruct & Crush NetworkErinc Merdivan, Mohammad Reza Loghmani, Matthieu Geist. 4551-4559 [doi]
- Streaming Robust Submodular Maximization: A Partitioned Thresholding ApproachSlobodan Mitrovic, Ilija Bogunovic, Ashkan Norouzi-Fard, Jakub Tarnawski, Volkan Cevher. 4560-4569 [doi]
- Simple strategies for recovering inner products from coarsely quantized random projectionsPing Li 0001, Martin Slawski. 4570-4579 [doi]
- Discovering Potential Correlations via HypercontractivityHyeji Kim, Weihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath. 4580-4590 [doi]
- Doubly Stochastic Variational Inference for Deep Gaussian ProcessesHugh Salimbeni, Marc Peter Deisenroth. 4591-4602 [doi]
- Ranking Data with Continuous Labels through Oriented Recursive PartitionsStéphan Clémençon, Mastane Achab. 4603-4611 [doi]
- Scalable Model Selection for Belief NetworksZhao Song, Yusuke Muraoka, Ryohei Fujimaki, Lawrence Carin. 4612-4622 [doi]
- Targeting EEG/LFP Synchrony with Neural NetsYitong Li, michael Murias, samantha Major, Geraldine Dawson, Kafui Dzirasa, Lawrence Carin, David E. Carlson. 4623-4633 [doi]
- Near-Optimal Edge Evaluation in Explicit Generalized Binomial GraphsSanjiban Choudhury, Shervin Javdani, Siddhartha Srinivasa, Sebastian Scherer. 4634-4644 [doi]
- Non-Stationary Spectral KernelsSami Remes, Markus Heinonen, Samuel Kaski. 4645-4654 [doi]
- Overcoming Catastrophic Forgetting by Incremental Moment MatchingSang-Woo Lee, Jin-Hwa Kim, Jaehyun Jun, Jung-Woo Ha, Byoung-Tak Zhang. 4655-4665 [doi]
- Balancing information exposure in social networksKiran Garimella, Aristides Gionis, Nikos Parotsidis, Nikolaj Tatti. 4666-4674 [doi]
- SafetyNets: Verifiable Execution of Deep Neural Networks on an Untrusted CloudZahra Ghodsi, Tianyu Gu, Siddharth Garg. 4675-4684 [doi]
- Query Complexity of Clustering with Side InformationArya Mazumdar, Barna Saha. 4685-4696 [doi]
- QMDP-Net: Deep Learning for Planning under Partial ObservabilityPéter Karkus, David Hsu, Wee Sun Lee. 4697-4707 [doi]
- Robust Optimization for Non-Convex ObjectivesRobert S. Chen, Brendan Lucier, Yaron Singer, Vasilis Syrgkanis. 4708-4717 [doi]
- Thy Friend is My Friend: Iterative Collaborative Filtering for Sparse Matrix EstimationChristian Borgs, Jennifer T. Chayes, Christina E. Lee, Devavrat Shah. 4718-4729 [doi]
- Adaptive Classification for Prediction Under a BudgetFeng Nan, Venkatesh Saligrama. 4730-4740 [doi]
- Convergence rates of a partition based Bayesian multivariate density estimation methodLinxi Liu, Dangna Li, Wing Hung Wong. 4741-4749 [doi]
- Affine-Invariant Online Optimization and the Low-rank Experts ProblemTomer Koren, Roi Livni. 4750-4758 [doi]
- Beyond Worst-case: A Probabilistic Analysis of Affine Policies in Dynamic OptimizationOmar El Housni, Vineet Goyal. 4759-4767 [doi]
- A Unified Approach to Interpreting Model PredictionsScott M. Lundberg, Su-In Lee. 4768-4777 [doi]
- Stochastic Approximation for Canonical Correlation AnalysisRaman Arora, Teodor Vanislavov Marinov, Poorya Mianjy, Nati Srebro. 4778-4787 [doi]
- Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practiceJeffrey Pennington, Samuel S. Schoenholz, Surya Ganguli. 4788-4798 [doi]
- Sample and Computationally Efficient Learning Algorithms under S-Concave DistributionsMaria-Florina Balcan, Hongyang Zhang. 4799-4808 [doi]
- Scalable Variational Inference for Dynamical SystemsNico S. Gorbach, Stefan Bauer, Joachim M. Buhmann. 4809-4818 [doi]
- Context Selection for Embedding ModelsLi-Ping Liu, Francisco J. R. Ruiz, Susan Athey, David M. Blei. 4819-4828 [doi]
- Working hard to know your neighbor's margins: Local descriptor learning lossAnastasya Mishchuk, Dmytro Mishkin, Filip Radenovic, Jiri Matas. 4829-4840 [doi]
- Accelerated Stochastic Greedy Coordinate Descent by Soft Thresholding Projection onto SimplexChao-Bing Song, Shaobo Cui, Yong Jiang, Shu-Tao Xia. 4841-4850 [doi]
- Multi-Task Learning for Contextual BanditsAniket Anand Deshmukh, Ürün Dogan, Clayton Scott. 4851-4859 [doi]
- Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain SurgeonXin Dong, Shangyu Chen, Sinno Jialin Pan. 4860-4874 [doi]
- Accelerated First-order Methods for Geodesically Convex Optimization on Riemannian ManifoldsYuanyuan Liu, Fanhua Shang, James Cheng, Hong Cheng, Licheng Jiao. 4875-4884 [doi]
- Selective Classification for Deep Neural NetworksYonatan Geifman, Ran El-Yaniv. 4885-4894 [doi]
- Minimax Estimation of Bandable Precision MatricesAddison Hu, Sahand Negahban. 4895-4903 [doi]
- Monte-Carlo Tree Search by Best Arm IdentificationEmilie Kaufmann, Wouter M. Koolen. 4904-4913 [doi]
- Group Additive Structure Identification for Kernel Nonparametric RegressionChao Pan, Michael Zhu. 4914-4923 [doi]
- Fast, Sample-Efficient Algorithms for Structured Phase RetrievalGauri Jagatap, Chinmay Hegde. 4924-4934 [doi]
- Hash Embeddings for Efficient Word RepresentationsDan Svenstrup, Jonas Meinertz Hansen, Ole Winther. 4935-4943 [doi]
- Online Learning for Multivariate Hawkes ProcessesYingxiang Yang, Jalal Etesami, Niao He, Negar Kiyavash. 4944-4953 [doi]
- Maximum Margin Interval TreesAlexandre Drouin, Toby Hocking, François Laviolette. 4954-4963 [doi]
- DropoutNet: Addressing Cold Start in Recommender SystemsMaksims Volkovs, Guang Wei Yu, Tomi Poutanen. 4964-4973 [doi]
- A simple neural network module for relational reasoningAdam Santoro, David Raposo, David G. T. Barrett, Mateusz Malinowski, Razvan Pascanu, Peter Battaglia, Tim Lillicrap. 4974-4983 [doi]
- Q-LDA: Uncovering Latent Patterns in Text-based Sequential Decision ProcessesJianshu Chen, Chong Wang, Lin Xiao, Ji He, Lihong Li 0001, Li Deng. 4984-4993 [doi]
- Online Reinforcement Learning in Stochastic GamesChen-Yu Wei, Yi-Te Hong, Chi-Jen Lu. 4994-5004 [doi]
- Position-based Multiple-play Bandit Problem with Unknown Position BiasJunpei Komiyama, Junya Honda, Akiko Takeda. 5005-5015 [doi]
- Active Exploration for Learning Symbolic RepresentationsGarrett Andersen, George Konidaris. 5016-5026 [doi]
- Clone MCMC: Parallel High-Dimensional Gaussian Gibbs SamplingAndrei-Cristian Barbos, Francois Caron, Jean-François Giovannelli, Arnaud Doucet. 5027-5035 [doi]
- Fair Clustering Through FairletsFlavio Chierichetti, Ravi Kumar 0001, Silvio Lattanzi, Sergei Vassilvitskii. 5036-5044 [doi]
- Polynomial time algorithms for dual volume samplingChengtao Li, Stefanie Jegelka, Suvrit Sra. 5045-5054 [doi]
- Hindsight Experience ReplayMarcin Andrychowicz, Dwight Crow, Alex Ray, Jonas Schneider, Rachel Fong, Peter Welinder, Bob McGrew, Josh Tobin, Pieter Abbeel, Wojciech Zaremba. 5055-5065 [doi]
- Stochastic and Adversarial Online Learning without HyperparametersAshok Cutkosky, Kwabena A. Boahen. 5066-5074 [doi]
- Teaching Machines to Describe Images with Natural Language FeedbackHuan Ling, Sanja Fidler. 5075-5085 [doi]
- Perturbative Black Box Variational InferenceRobert Bamler, Cheng Zhang 0005, Manfred Opper, Stephan Mandt. 5086-5094 [doi]
- GibbsNet: Iterative Adversarial Inference for Deep Graphical ModelsAlex Lamb, R. Devon Hjelm, Yaroslav Ganin, Joseph Paul Cohen, Aaron C. Courville, Yoshua Bengio. 5095-5104 [doi]
- PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric SpaceCharles Ruizhongtai Qi, Li Yi, Hao Su, Leonidas J. Guibas. 5105-5114 [doi]
- Regularizing Deep Neural Networks by Noise: Its Interpretation and OptimizationHyeonwoo Noh, Tackgeun You, Jonghwan Mun, Bohyung Han. 5115-5124 [doi]
- Learning Graph Representations with Embedding PropagationAlberto García-Durán, Mathias Niepert. 5125-5136 [doi]
- Efficient Modeling of Latent Information in Supervised Learning using Gaussian ProcessesZhenwen Dai, Mauricio A. Álvarez, Neil D. Lawrence. 5137-5145 [doi]
- A-NICE-MC: Adversarial Training for MCMCJiaming Song, Shengjia Zhao, Stefano Ermon. 5146-5156 [doi]
- Excess Risk Bounds for the Bayes Risk using Variational Inference in Latent Gaussian ModelsRishit Sheth, Roni Khardon. 5157-5167 [doi]
- Real-Time Bidding with Side InformationArthur Flajolet, Patrick Jaillet. 5168-5178 [doi]
- Saliency-based Sequential Image Attention with Multiset PredictionSean Welleck, Jialin Mao, KyungHyun Cho, Zheng Zhang. 5179-5189 [doi]
- Variational Inference for Gaussian Process Models with Linear ComplexityChing-An Cheng, Byron Boots. 5190-5200 [doi]
- K-Medoids For K-Means SeedingJames Newling, François Fleuret. 5201-5209 [doi]
- Identifying Outlier Arms in Multi-Armed BanditHonglei Zhuang, Chi Wang 0001, Yifan Wang. 5210-5219 [doi]
- Online Learning with Transductive RegretScott Yang, Mehryar Mohri. 5220-5230 [doi]
- Riemannian approach to batch normalizationMinhyung Cho, Jaehyung Lee. 5231-5241 [doi]
- Self-supervised Learning of Motion CaptureHsiao-Yu Tung, Hsiao-Wei Tung, Ersin Yumer, Katerina Fragkiadaki. 5242-5252 [doi]
- Triangle Generative Adversarial NetworksZhe Gan, Liqun Chen, Weiyao Wang, Yunchen Pu, Yizhe Zhang, Hao Liu, Chunyuan Li, Lawrence Carin. 5253-5262 [doi]
- PRUNE: Preserving Proximity and Global Ranking for Network EmbeddingYi-An Lai, Chin-Chi Hsu, Wen-Hao Chen, Mi-Yen Yeh, Shou-de Lin. 5263-5272 [doi]
- Bayesian Optimization with GradientsJian Wu, Matthias Poloczek, Andrew Gordon Wilson, Peter I. Frazier. 5273-5284 [doi]
- Second-order Optimization for Deep Reinforcement Learning using Kronecker-factored ApproximationYuhuai Wu, Elman Mansimov, Roger B. Grosse, Shun Liao, Jimmy Ba. 5285-5294 [doi]
- Renyi Differential Privacy Mechanisms for Posterior SamplingJoseph Geumlek, Shuang Song, Kamalika Chaudhuri. 5295-5304 [doi]
- Online Learning with a HintOfer Dekel, Arthur Flajolet, Nika Haghtalab, Patrick Jaillet. 5305-5314 [doi]
- Identification of Gaussian Process State Space ModelsStefanos Eleftheriadis, Tom Nicholson, Marc Peter Deisenroth, James Hensman. 5315-5325 [doi]
- Robust Imitation of Diverse BehaviorsZiyu Wang 0001, Josh S. Merel, Scott E. Reed, Nando de Freitas, Gregory Wayne, Nicolas Heess. 5326-5335 [doi]
- Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient DescentXiangru Lian, Ce Zhang, Huan Zhang, Cho-Jui Hsieh, Wei Zhang, Ji Liu. 5336-5346 [doi]
- Local Aggregative GamesVikas K. Garg, Tommi S. Jaakkola. 5347-5357 [doi]
- A Sample Complexity Measure with Applications to Learning Optimal AuctionsVasilis Syrgkanis. 5358-5365 [doi]
- Thinking Fast and Slow with Deep Learning and Tree SearchThomas Anthony, Zheng Tian, David Barber. 5366-5376 [doi]
- EEG-GRAPH: A Factor-Graph-Based Model for Capturing Spatial, Temporal, and Observational Relationships in ElectroencephalogramsYogatheesan Varatharajah, Min Jin Chong, Krishnakant Saboo, Brent M. Berry, Benjamin H. Brinkmann, Gregory A. Worrell, Ravishankar K. Iyer. 5377-5386 [doi]
- Improving the Expected Improvement AlgorithmChao Qin, Diego Klabjan, Daniel Russo 0001. 5387-5397 [doi]
- Hybrid Reward Architecture for Reinforcement LearningHarm van Seijen, Mehdi Fatemi, Romain Laroche, Joshua Romoff, Tavian Barnes, Jeffrey Tsang. 5398-5408 [doi]
- Approximate Supermodularity Bounds for Experimental DesignLuiz F. O. Chamon, Alejandro Ribeiro. 5409-5418 [doi]
- Maximizing Subset Accuracy with Recurrent Neural Networks in Multi-label ClassificationJinseok Nam, Eneldo Loza Mencía, Hyunwoo J. Kim, Johannes Fürnkranz. 5419-5429 [doi]
- AdaGAN: Boosting Generative ModelsIlya O. Tolstikhin, Sylvain Gelly, Olivier Bousquet, Carl-Johann Simon-Gabriel, Bernhard Schölkopf. 5430-5439 [doi]
- Straggler Mitigation in Distributed Optimization Through Data EncodingCan Karakus, Yifan Sun, Suhas N. Diggavi, Wotao Yin. 5440-5448 [doi]
- Multi-View Decision Processes: The Helper-AI ProblemChristos Dimitrakakis, David C. Parkes, Goran Radanovic, Paul Tylkin. 5449-5458 [doi]
- A Greedy Approach for Budgeted Maximum Inner Product SearchHsiang-Fu Yu, Cho-Jui Hsieh, Qi Lei, Inderjit S. Dhillon. 5459-5468 [doi]
- SVD-Softmax: Fast Softmax Approximation on Large Vocabulary Neural NetworksKyuhong Shim, MinJae Lee, Iksoo Choi, Yoonho Boo, Wonyong Sung. 5469-5479 [doi]
- Plan, Attend, Generate: Planning for Sequence-to-Sequence ModelsÇaglar Gülçehre, Francis Dutil, Adam Trischler, Yoshua Bengio. 5480-5489 [doi]
- Task-based End-to-end Model Learning in Stochastic OptimizationPriya L. Donti, J. Zico Kolter, Brandon Amos. 5490-5500 [doi]
- ALICE: Towards Understanding Adversarial Learning for Joint Distribution MatchingChunyuan Li, Hao Liu, Changyou Chen, Yunchen Pu, Liqun Chen, Ricardo Henao, Lawrence Carin. 5501-5509 [doi]
- Finite sample analysis of the GTD Policy Evaluation Algorithms in Markov SettingYue Wang, Wei Chen, Yuting Liu, Zhiming Ma, Tie-Yan Liu. 5510-5519 [doi]
- On the Complexity of Learning Neural NetworksLe Song, Santosh Vempala, John Wilmes, Bo Xie 0002. 5520-5528 [doi]
- Hierarchical Implicit Models and Likelihood-Free Variational InferenceDustin Tran, Rajesh Ranganath, David M. Blei. 5529-5539 [doi]
- Semi-supervised Learning with GANs: Manifold Invariance with Improved InferenceAbhishek Kumar, Prasanna Sattigeri, Tom Fletcher. 5540-5550 [doi]
- Approximation and Convergence Properties of Generative Adversarial LearningShuang Liu, Olivier Bousquet, Kamalika Chaudhuri. 5551-5559 [doi]
- From Bayesian Sparsity to Gated Recurrent NetsHao He, Bo Xin, Satoshi Ikehata, David P. Wipf. 5560-5570 [doi]
- Min-Max PropagationChristopher Srinivasa, Inmar E. Givoni, Siamak Ravanbakhsh, Brendan J. Frey. 5571-5579 [doi]
- What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?Alex Kendall, Yarin Gal. 5580-5590 [doi]
- Gradient descent GAN optimization is locally stableVaishnavh Nagarajan, J. Zico Kolter. 5591-5600 [doi]
- Toward Robustness against Label Noise in Training Deep Discriminative Neural NetworksArash Vahdat. 5601-5610 [doi]
- Dualing GANsYujia Li, Alexander G. Schwing, Kuan-Chieh Wang, Richard S. Zemel. 5611-5621 [doi]
- Deep Learning for Precipitation Nowcasting: A Benchmark and A New ModelXingjian Shi, Zhihan Gao, Leonard Lausen, Hao Wang 0014, Dit-Yan Yeung, Wai-Kin Wong, Wang-chun Woo. 5622-5632 [doi]
- Do Deep Neural Networks Suffer from Crowding?Anna Volokitin, Gemma Roig, Tomaso A. Poggio. 5633-5643 [doi]
- Learning from Complementary LabelsTakashi Ishida, Gang Niu, Weihua Hu, Masashi Sugiyama. 5644-5654 [doi]
- Online control of the false discovery rate with decaying memoryAaditya Ramdas, Fanny Yang, Martin J. Wainwright, Michael I. Jordan. 5655-5664 [doi]
- Learning from uncertain curves: The 2-Wasserstein metric for Gaussian processesAnton Mallasto, Aasa Feragen. 5665-5674 [doi]
- Discriminative State Space ModelsVitaly Kuznetsov, Mehryar Mohri. 5675-5683 [doi]
- On Fairness and CalibrationGeoff Pleiss, Manish Raghavan, Felix Wu, Jon M. Kleinberg, Kilian Q. Weinberger. 5684-5693 [doi]
- Imagination-Augmented Agents for Deep Reinforcement LearningSébastien Racanière, Theophane Weber, David P. Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adrià Puigdomènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, Razvan Pascanu, Peter Battaglia, Demis Hassabis, David Silver, Daan Wierstra. 5694-5705 [doi]
- Extracting low-dimensional dynamics from multiple large-scale neural population recordings by learning to predict correlationsMarcel Nonnenmacher, Srinivas C. Turaga, Jakob H. Macke. 5706-5716 [doi]
- Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement LearningChristoph Dann, Tor Lattimore, Emma Brunskill. 5717-5727 [doi]
- Gradients of Generative Models for Improved Discriminative Analysis of Tandem Mass SpectraJohn T. Halloran, David M. Rocke. 5728-5737 [doi]
- Asynchronous Parallel Coordinate Minimization for MAP InferenceOfer Meshi, Alexander G. Schwing. 5738-5748 [doi]
- Multiscale Quantization for Fast Similarity SearchXiang Wu, Ruiqi Guo, Ananda Theertha Suresh, Sanjiv Kumar, Daniel N. Holtmann-Rice, David Simcha, Felix X. Yu. 5749-5757 [doi]
- Diverse and Accurate Image Description Using a Variational Auto-Encoder with an Additive Gaussian Encoding SpaceLiwei Wang 0009, Alexander G. Schwing, Svetlana Lazebnik. 5758-5768 [doi]
- Improved Training of Wasserstein GANsIshaan Gulrajani, Faruk Ahmed, Martín Arjovsky, Vincent Dumoulin, Aaron C. Courville. 5769-5779 [doi]
- Learning Populations of ParametersKevin Tian, Weihao Kong, Gregory Valiant. 5780-5789 [doi]
- Clustering with Noisy QueriesArya Mazumdar, Barna Saha. 5790-5801 [doi]
- Higher-Order Total Variation Classes on Grids: Minimax Theory and Trend Filtering MethodsVeeranjaneyulu Sadhanala, Yu-Xiang Wang, James Sharpnack, Ryan J. Tibshirani. 5802-5812 [doi]
- Training Quantized Nets: A Deeper UnderstandingHao Li, Soham De, Zheng Xu 0002, Christoph Studer, Hanan Samet, Tom Goldstein. 5813-5823 [doi]
- Permutation-based Causal Inference Algorithms with InterventionsYuhao Wang, Liam Solus, Karren Yang, Caroline Uhler. 5824-5833 [doi]
- Time-dependent spatially varying graphical models, with application to brain fMRI data analysisKristjan Greenewald, Seyoung Park, Shuheng Zhou, Alexander Giessing. 5834-5842 [doi]
- Gradient Methods for Submodular MaximizationS. Hamed Hassani, Mahdi Soltanolkotabi, Amin Karbasi. 5843-5853 [doi]
- Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex OptimizationAhmet Alacaoglu, Quoc Tran-Dinh, Olivier Fercoq, Volkan Cevher. 5854-5863 [doi]
- The Importance of Communities for Learning to InfluenceEric Balkanski, Nicole Immorlica, Yaron Singer. 5864-5873 [doi]
- Multiplicative Weights Update with Constant Step-Size in Congestion Games: Convergence, Limit Cycles and ChaosGerasimos Palaiopanos, Ioannis Panageas, Georgios Piliouras. 5874-5884 [doi]
- Learning Neural Representations of Human Cognition across Many fMRI StudiesArthur Mensch, Julien Mairal, Danilo Bzdok, Bertrand Thirion, Gaël Varoquaux. 5885-5895 [doi]
- A KL-LUCB algorithm for Large-Scale CrowdsourcingErvin Tanczos, Robert Nowak, Bob Mankoff. 5896-5905 [doi]
- Collaborative Deep Learning in Fixed Topology NetworksZhanhong Jiang, Aditya Balu, Chinmay Hegde, Soumik Sarkar. 5906-5916 [doi]
- Fast-Slow Recurrent Neural NetworksAsier Mujika, Florian Meier, Angelika Steger. 5917-5926 [doi]
- Learning Disentangled Representations with Semi-Supervised Deep Generative ModelsSiddharth Narayanaswamy, Brooks Paige, Jan-Willem van de Meent, Alban Desmaison, Noah D. Goodman, Pushmeet Kohli, Frank D. Wood, Philip H. S. Torr. 5927-5937 [doi]
- Self-Supervised Intrinsic Image DecompositionMichael Janner, Jiajun Wu 0001, Tejas D. Kulkarni, Ilker Yildirim, Josh Tenenbaum. 5938-5948 [doi]
- Exploring Generalization in Deep LearningBehnam Neyshabur, Srinadh Bhojanapalli, David McAllester, Nati Srebro. 5949-5958 [doi]
- A framework for Multi-A(rmed)/B(andit) Testing with Online FDR ControlFanny Yang, Aaditya Ramdas, Kevin G. Jamieson, Martin J. Wainwright. 5959-5968 [doi]
- Fader Networks: Manipulating Images by Sliding AttributesGuillaume Lample, Neil Zeghidour, Nicolas Usunier, Antoine Bordes, Ludovic Denoyer, Marc'Aurelio Ranzato. 5969-5978 [doi]
- Action Centered Contextual BanditsKristjan Greenewald, Ambuj Tewari, Susan A. Murphy, Predrag V. Klasnja. 5979-5987 [doi]
- Estimating Mutual Information for Discrete-Continuous MixturesWeihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath. 5988-5999 [doi]
- Attention is All you NeedAshish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, Illia Polosukhin. 6000-6010 [doi]
- Recurrent Ladder NetworksIsabeau Prémont-Schwarz, Alexander Ilin, Tele Hao, Antti Rasmus, Rinu Boney, Harri Valpola. 6011-6021 [doi]
- Parameter-Free Online Learning via Model SelectionDylan J. Foster, Satyen Kale, Mehryar Mohri, Karthik Sridharan. 6022-6032 [doi]
- Bregman Divergence for Stochastic Variance Reduction: Saddle-Point and Adversarial PredictionZhan Shi, Xinhua Zhang, Yaoliang Yu. 6033-6043 [doi]
- Unbounded cache model for online language modeling with open vocabularyEdouard Grave, Moustapha Cissé, Armand Joulin. 6044-6054 [doi]
- Predictive State Recurrent Neural NetworksCarlton Downey, Ahmed Hefny, Byron Boots, Geoffrey J. Gordon, Boyue Li. 6055-6066 [doi]
- Early stopping for kernel boosting algorithms: A general analysis with localized complexitiesYuting Wei, Fanny Yang, Martin J. Wainwright. 6067-6077 [doi]
- SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and InterpretabilityMaithra Raghu, Justin Gilmer, Jason Yosinski, Jascha Sohl-Dickstein. 6078-6087 [doi]
- Convolutional Phase RetrievalQing Qu, Yuqian Zhang, Yonina Eldar, John Wright. 6088-6098 [doi]
- Estimating High-dimensional Non-Gaussian Multiple Index Models via Stein's LemmaZhuoran Yang, Krishnakumar Balasubramanian, Zhaoran Wang, Han Liu. 6099-6108 [doi]
- Gaussian Quadrature for Kernel FeaturesTri Dao, Christopher De Sa, Christopher Ré. 6109-6119 [doi]
- Value Prediction NetworkJunhyuk Oh, Satinder Singh, Honglak Lee. 6120-6130 [doi]
- A Learning Error Analysis for Structured Prediction with Approximate InferenceYuanbin Wu, Man Lan, Shiliang Sun, Qi Zhang, Xuanjing Huang. 6131-6141 [doi]
- Efficient Second-Order Online Kernel Learning with Adaptive EmbeddingDaniele Calandriello, Alessandro Lazaric, Michal Valko. 6142-6151 [doi]
- Implicit Regularization in Matrix FactorizationSuriya Gunasekar, Blake E. Woodworth, Srinadh Bhojanapalli, Behnam Neyshabur, Nati Srebro. 6152-6160 [doi]
- Optimal Shrinkage of Singular Values Under Random Data ContaminationDanny Barash, Matan Gavish. 6161-6171 [doi]
- Countering Feedback Delays in Multi-Agent Learning