Table of Contents

• Deep Statistical SolversBalthazar Donon, Zhengying Liu, Wenzhuo Liu, Isabelle Guyon, Antoine Marot, Marc Schoenauer. [doi]
• Sample complexity and effective dimension for regression on manifoldsAndrew D. McRae, Justin Romberg, Mark A. Davenport. [doi]
• Federated Accelerated Stochastic Gradient DescentHonglin Yuan, Tengyu Ma. [doi]
• GAN Memory with No ForgettingYulai Cong, Miaoyun Zhao, Jianqiao Li, Sijia Wang, Lawrence Carin. [doi]
• Investigating Gender Bias in Language Models Using Causal Mediation AnalysisJesse Vig, Sebastian Gehrmann, Yonatan Belinkov, Sharon Qian, Daniel Nevo, Yaron Singer, Stuart M. Shieber. [doi]
• Minimax Bounds for Generalized Linear ModelsKuan-Yun Lee, Thomas A. Courtade. [doi]
• Meta-NeighborhoodsSiyuan Shan, Yang Li, Junier B. Oliva. [doi]
• Reasoning about Uncertainties in Discrete-Time Dynamical Systems using Polynomial FormsSriram Sankaranarayanan 0001, Yi Chou, Eric Goubault, Sylvie Putot. [doi]
• Domain Generalization via Entropy RegularizationShanshan Zhao, Mingming Gong, Tongliang Liu, Huan Fu, Dacheng Tao. [doi]
• Automatically Learning Compact Quality-aware Surrogates for Optimization ProblemsKai Wang 0040, Bryan Wilder, Andrew Perrault, Milind Tambe. [doi]
• Is normalization indispensable for training deep neural network?Jie Shao, Kai Hu, Changhu Wang, Xiangyang Xue, Bhiksha Raj. [doi]
• Debugging Tests for Model ExplanationsJulius Adebayo, Michael Muelly, Ilaria Liccardi, Been Kim. [doi]
• Variational Bayesian Monte Carlo with Noisy LikelihoodsLuigi Acerbi. [doi]
• Estimation of Skill Distribution from a TournamentAli Jadbabaie, Anuran Makur, Devavrat Shah. [doi]
• Neuronal Gaussian Process RegressionJohannes Friedrich. [doi]
• Adversarial robustness via robust low rank representationsPranjal Awasthi, Himanshu Jain, Ankit Singh Rawat, Aravindan Vijayaraghavan. [doi]
• Synthesizing Tasks for Block-based ProgrammingUmair Z. Ahmed, Maria Christakis, Aleksandr Efremov, Nigel Fernandez, Ahana Ghosh, Abhik Roychoudhury, Adish Singla. [doi]
• Generalized Hindsight for Reinforcement LearningAlexander C. Li, Lerrel Pinto, Pieter Abbeel. [doi]
• The Pitfalls of Simplicity Bias in Neural NetworksHarshay Shah, Kaustav Tamuly, Aditi Raghunathan, Prateek Jain 0002, Praneeth Netrapalli. [doi]
• Evidential Sparsification of Multimodal Latent Spaces in Conditional Variational AutoencodersMasha Itkina, Boris Ivanovic, Ransalu Senanayake, Mykel J. Kochenderfer, Marco Pavone. [doi]
• Adversarially Robust Few-Shot Learning: A Meta-Learning ApproachMicah Goldblum, Liam Fowl, Tom Goldstein. [doi]
• Handling Missing Data with Graph Representation LearningJiaxuan You, Xiaobai Ma, Daisy Yi Ding, Mykel J. Kochenderfer, Jure Leskovec. [doi]
• Belief Propagation Neural NetworksJonathan Kuck, Shuvam Chakraborty, Hao Tang, Rachel Luo, Jiaming Song, Ashish Sabharwal, Stefano Ermon. [doi]
• Identifying signal and noise structure in neural population activity with Gaussian process factor modelsStephen L. Keeley, Mikio Aoi, Yiyi Yu, Spencer L. Smith, Jonathan W. Pillow. [doi]
• Denoised Smoothing: A Provable Defense for Pretrained ClassifiersHadi Salman, Mingjie Sun, Greg Yang, Ashish Kapoor, J. Zico Kolter. [doi]
• Semi-Supervised Partial Label Learning via Confidence-Rated Margin MaximizationWei Wang, Min-Ling Zhang. [doi]
• Hyperparameter Ensembles for Robustness and Uncertainty QuantificationFlorian Wenzel, Jasper Snoek, Dustin Tran, Rodolphe Jenatton. [doi]
• Online Structured Meta-learningHuaxiu Yao, Yingbo Zhou, Mehrdad Mahdavi, Zhenhui Li, Richard Socher, Caiming Xiong. [doi]
• PLLay: Efficient Topological Layer based on Persistent LandscapesKwangho Kim, Jisu Kim, Manzil Zaheer, Joon Sik Kim, Frédéric Chazal, Larry A. Wasserman. [doi]
• Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clusteringMeng Liu, David F. Gleich. [doi]
• Approximation Based Variance Reduction for Reparameterization GradientsTomas Geffner, Justin Domke. [doi]
• Learning efficient task-dependent representations with synaptic plasticityColin Bredenberg, Eero P. Simoncelli, Cristina Savin. [doi]
• How do fair decisions fare in long-term qualification?Xueru Zhang, Ruibo Tu, Yang Liu, Mingyan Liu, Hedvig Kjellström, Kun Zhang 0001, Cheng Zhang 0005. [doi]
• Field-wise Learning for Multi-field Categorical DataZhibin Li 0002, Jian Zhang 0002, Yongshun Gong, Yazhou Yao, Qiang Wu 0001. [doi]
• Improving Policy-Constrained Kidney Exchange via Pre-ScreeningDuncan C. McElfresh, Michael J. Curry, Tuomas Sandholm, John Dickerson 0001. [doi]
• On the Power of Louvain in the Stochastic Block ModelVincent Cohen-Addad, Adrian Kosowski, Frederik Mallmann-Trenn, David Saulpic. [doi]
• Learning Some Popular Gaussian Graphical Models without Condition Number BoundsJonathan A. Kelner, Frederic Koehler, Raghu Meka, Ankur Moitra. [doi]
• Adversarial Self-Supervised Contrastive LearningMinseon Kim, Jihoon Tack, Sung Ju Hwang. [doi]
• Compositional Generalization via Neural-Symbolic Stack MachinesXinyun Chen, Chen Liang, Adams Wei Yu, Dawn Song, Denny Zhou. [doi]
• Global Convergence and Variance Reduction for a Class of Nonconvex-Nonconcave Minimax ProblemsJunchi Yang, Negar Kiyavash, Niao He. [doi]
• Triple descent and the two kinds of overfitting: where & why do they appear?Stéphane d'Ascoli, Levent Sagun, Giulio Biroli. [doi]
• Unfolding the Alternating Optimization for Blind Super ResolutionZhengxiong Luo, Yan Huang 0008, Shang Li, Liang Wang, Tieniu Tan. [doi]
• Self-supervised Co-Training for Video Representation LearningTengda Han, Weidi Xie, Andrew Zisserman. [doi]
• Bridging the Gap between Sample-based and One-shot Neural Architecture Search with BONASHan Shi, Renjie Pi, Hang Xu, Zhenguo Li, James T. Kwok, Tong Zhang. [doi]
• Finite-Time Analysis for Double Q-learningHuaqing Xiong, Lin Zhao, Yingbin Liang, Wei Zhang. [doi]
• Bayesian Attention ModulesXinjie Fan, Shujian Zhang, Bo Chen 0001, Mingyuan Zhou. [doi]
• The Implications of Local Correlation on Learning Some Deep FunctionsEran Malach, Shai Shalev-Shwartz. [doi]
• Exploiting MMD and Sinkhorn Divergences for Fair and Transferable Representation LearningLuca Oneto, Michele Donini, Giulia Luise, Carlo Ciliberto, Andreas Maurer, Massimiliano Pontil. [doi]
• The Diversified Ensemble Neural NetworkShaofeng Zhang, Meng Liu, Junchi Yan. [doi]
• Empirical Likelihood for Contextual BanditsNikos Karampatziakis, John Langford 0001, Paul Mineiro. [doi]
• Every View Counts: Cross-View Consistency in 3D Object Detection with Hybrid-Cylindrical-Spherical VoxelizationQi Chen, Lin Sun, Ernest Cheung, Alan L. Yuille. [doi]
• Bayesian Probabilistic Numerical Integration with Tree-Based ModelsHarrison Zhu, Xing Liu, Ruya Kang, Zhichao Shen, Seth Flaxman, François-Xavier Briol. [doi]
• SnapBoost: A Heterogeneous Boosting MachineThomas P. Parnell, Andreea Anghel, Malgorzata Lazuka, Nikolas Ioannou, Sebastian Kurella, Peshal Agarwal, Nikolaos Papandreou, Haralampos Pozidis. [doi]
• Learning Global Transparent Models consistent with Local Contrastive ExplanationsTejaswini Pedapati, Avinash Balakrishnan, Karthikeyan Shanmugam, Amit Dhurandhar. [doi]
• No-Regret Learning and Mixed Nash Equilibria: They Do Not MixEmmanouil-Vasileios Vlatakis-Gkaragkounis, Lampros Flokas, Thanasis Lianeas, Panayotis Mertikopoulos, Georgios Piliouras. [doi]
• Robust large-margin learning in hyperbolic spaceMelanie Weber 0001, Manzil Zaheer, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar. [doi]
• Probably Approximately Correct Constrained LearningLuiz F. O. Chamon, Alejandro Ribeiro. [doi]
• Improving Generalization in Reinforcement Learning with Mixture RegularizationKaixin Wang, Bingyi Kang, Jie Shao, Jiashi Feng. [doi]
• Optimal Learning from Verified Training DataNick Bishop, Long Tran-Thanh, Enrico Gerding. [doi]
• Exploiting weakly supervised visual patterns to learn from partial annotationsKaustav Kundu, Joseph Tighe. [doi]
• Learnability with Indirect Supervision SignalsKaifu Wang, Qiang Ning, Dan Roth. [doi]
• Uncertainty-Aware Learning for Zero-Shot Semantic SegmentationPing Hu, Stan Sclaroff, Kate Saenko. [doi]
• Implicit Distributional Reinforcement LearningYuguang Yue, Zhendong Wang, Mingyuan Zhou. [doi]
• Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize ScalingYu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos. [doi]
• MuSCLE: Multi Sweep Compression of LiDAR using Deep Entropy ModelsSourav Biswas, Jerry Liu, Kelvin Wong, Shenlong Wang, Raquel Urtasun. [doi]
• Heavy-tailed Representations, Text Polarity Classification & Data AugmentationHamid Jalalzai, Pierre Colombo, Chloé Clavel, Éric Gaussier, Giovanna Varni, Emmanuel Vignon, Anne Sabourin. [doi]
• Deeply Learned Spectral Total Variation DecompositionTamara G. Grossmann, Yury Korolev, Guy Gilboa, Carola B. Schönlieb. [doi]
• Subgroup-based Rank-1 Lattice Quasi-Monte CarloYueming Lyu, Yuan Yuan 0002, Ivor W. Tsang. [doi]
• Towards Safe Policy Improvement for Non-Stationary MDPsYash Chandak, Scott M. Jordan, Georgios Theocharous, Martha White, Philip S. Thomas. [doi]
• Zero-Resource Knowledge-Grounded Dialogue GenerationLinxiao Li, Can Xu, Wei Wu 0014, Yufan Zhao, Xueliang Zhao, Chongyang Tao. [doi]
• Model-based Adversarial Meta-Reinforcement LearningZichuan Lin, Garrett Thomas, Guangwen Yang, Tengyu Ma. [doi]
• Noise-Contrastive Estimation for Multivariate Point ProcessesHongyuan Mei, Tom Wan, Jason Eisner. [doi]
• Learning to Detect Objects with a 1 Megapixel Event CameraEtienne Perot, Pierre de Tournemire, Davide Nitti 0002, Jonathan Masci, Amos Sironi. [doi]
• Provably Efficient Reinforcement Learning with Kernel and Neural Function ApproximationsZhuoran Yang, Chi Jin, Zhaoran Wang, Mengdi Wang, Michael I. Jordan. [doi]
• Off-Policy Evaluation and Learning for External Validity under a Covariate ShiftMasatoshi Uehara, Masahiro Kato, Shota Yasui. [doi]
• Rotation-Invariant Local-to-Global Representation Learning for 3D Point CloudSeohyun Kim, Jaeyoo Park, Bohyung Han. [doi]
• Graph Meta Learning via Local SubgraphsKexin Huang, Marinka Zitnik. [doi]
• Adam with Bandit Sampling for Deep LearningRui Liu, Tianyi Wu, Barzan Mozafari. [doi]
• Learning Manifold Implicitly via Explicit Heat-Kernel LearningYufan Zhou, Changyou Chen, Jinhui Xu 0001. [doi]
• Entropic Causal Inference: Identifiability and Finite Sample ResultsSpencer Compton, Murat Kocaoglu, Kristjan H. Greenewald, Dmitriy Katz. [doi]
• Learning by Minimizing the Sum of Ranked RangeShu Hu, Yiming Ying, Xin Wang 0045, Siwei Lyu. [doi]
• GANSpace: Discovering Interpretable GAN ControlsErik Härkönen, Aaron Hertzmann, Jaakko Lehtinen, Sylvain Paris. [doi]
• Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans by measuring error consistencyRobert Geirhos, Kristof Meding, Felix A. Wichmann. [doi]
• Robust Sequence Submodular MaximizationGamal Sallam, Zizhan Zheng, Jie Wu 0001, Bo Ji. [doi]
• Parametric Instance Classification for Unsupervised Visual Feature learningYue Cao 0001, Zhenda Xie, Bin Liu 0035, Yutong Lin, Zheng Zhang 0022, Han Hu 0004. [doi]
• MOPO: Model-based Offline Policy OptimizationTianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Y. Zou, Sergey Levine, Chelsea Finn, Tengyu Ma. [doi]
• StratLearner: Learning a Strategy for Misinformation Prevention in Social NetworksGuangmo Tong. [doi]
• Estimating decision tree learnability with polylogarithmic sample complexityGuy Blanc, Neha Gupta 0002, Jane Lange, Li-Yang Tan. [doi]
• Generalization bound of globally optimal non-convex neural network training: Transportation map estimation by infinite dimensional Langevin dynamicsTaiji Suzuki. [doi]
• Unsupervised Semantic Aggregation and Deformable Template Matching for Semi-Supervised LearningTao Han, Junyu Gao, Yuan Yuan 0001, Qi Wang 0009. [doi]
• Heuristic Domain AdaptationShuhao Cui, Xuan Jin, Shuhui Wang, Yuan He, Qingming Huang. [doi]
• Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication TimeJerry Li 0001, Guanghao Ye. [doi]
• Can Q-Learning with Graph Networks Learn a Generalizable Branching Heuristic for a SAT Solver?Vitaly Kurin, Saad Godil, Shimon Whiteson, Bryan Catanzaro. [doi]
• Automatic Perturbation Analysis for Scalable Certified Robustness and BeyondKaidi Xu, Zhouxing Shi, Huan Zhang 0001, Yihan Wang, Kai-Wei Chang, Minlie Huang, Bhavya Kailkhura, Xue Lin, Cho-Jui Hsieh. [doi]
• Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph CompletionZhanqiu Zhang, Jianyu Cai, Jie Wang 0005. [doi]
• Uncertainty Quantification for Inferring Hawkes NetworksHaoyun Wang, Liyan Xie, Alex Cuozzo, Simon Mak, Yao Xie 0002. [doi]
• Marginal Utility for Planning in Continuous or Large Discrete Action SpacesZaheen Farraz Ahmad, Levi Lelis, Michael Bowling. [doi]
• Pointer Graph NetworksPetar Velickovic, Lars Buesing, Matthew C. Overlan, Razvan Pascanu, Oriol Vinyals, Charles Blundell. [doi]
• Synthesize, Execute and Debug: Learning to Repair for Neural Program SynthesisKavi Gupta, Peter Ebert Christensen, Xinyun Chen, Dawn Song. [doi]
• Online Convex Optimization Over Erdos-Renyi Random NetworksJinlong Lei, Peng Yi, Yiguang Hong, Jie Chen, Guodong Shi. [doi]
• Modeling Shared responses in Neuroimaging Studies through MultiView ICAHugo Richard, Luigi Gresele, Aapo Hyvärinen, Bertrand Thirion, Alexandre Gramfort, Pierre Ablin. [doi]
• Unsupervised Text Generation by Learning from SearchJingjing Li, Zichao Li, Lili Mou, Xin Jiang, Michael R. Lyu, Irwin King. [doi]
• How hard is to distinguish graphs with graph neural networks?Andreas Loukas. [doi]
• Neural Networks Fail to Learn Periodic Functions and How to Fix ItZiyin Liu, Tilman Hartwig, Masahito Ueda. [doi]
• First-Order Methods for Large-Scale Market Equilibrium ComputationYuan Gao, Christian Kroer. [doi]
• Margins are Insufficient for Explaining Gradient BoostingAllan Grønlund, Lior Kamma, Kasper Green Larsen. [doi]
• Deep Archimedean CopulasChun Kai Ling, Fei Fang, J. Zico Kolter. [doi]
• A Statistical Mechanics Framework for Task-Agnostic Sample Design in Machine LearningBhavya Kailkhura, Jayaraman J. Thiagarajan, Qunwei Li, Jize Zhang, Yi Zhou, Timo Bremer. [doi]
• Estimation and Imputation in Probabilistic Principal Component Analysis with Missing Not At Random DataAude Sportisse, Claire Boyer, Julie Josse. [doi]
• Security Analysis of Safe and Seldonian Reinforcement Learning AlgorithmsPinar Ozisik, Philip S. Thomas. [doi]
• PRANK: motion Prediction based on RANKingYuriy Biktairov, Maxim Stebelev, Irina Rudenko, Oleh Shliazhko, Boris Yangel. [doi]
• A new inference approach for training shallow and deep generalized linear models of noisy interacting neuronsGabriel Mahuas, Giulio Isacchini, Olivier Marre, Ulisse Ferrari, Thierry Mora. [doi]
• Self-Supervised MultiModal Versatile NetworksJean-Baptiste Alayrac, Adrià Recasens, Rosalia Schneider, Relja Arandjelovic, Jason Ramapuram, Jeffrey De Fauw, Lucas Smaira, Sander Dieleman, Andrew Zisserman. [doi]
• Boosting First-Order Methods by Shifting Objective: New Schemes with Faster Worst-Case RatesKaiwen Zhou, Anthony Man-Cho So, James Cheng. [doi]
• A Topological Filter for Learning with Label NoisePengxiang Wu, Songzhu Zheng, Mayank Goswami 0001, Dimitris N. Metaxas, Chao Chen 0012. [doi]
• Theory-Inspired Path-Regularized Differential Network Architecture SearchPan Zhou, Caiming Xiong, Richard Socher, Steven Chu Hong Hoi. [doi]
• Sliding Window Algorithms for k-Clustering ProblemsMichele Borassi, Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam. [doi]
• FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPsAlekh Agarwal, Sham M. Kakade, Akshay Krishnamurthy, Wen Sun. [doi]
• Self-training Avoids Using Spurious Features Under Domain ShiftYining Chen, Colin Wei, Ananya Kumar, Tengyu Ma. [doi]
• A Simple and Efficient Smoothing Method for Faster Optimization and Local ExplorationKevin Scaman, Ludovic Dos Santos, Merwan Barlier, Igor Colin. [doi]
• Bayes Consistency vs. H-Consistency: The Interplay between Surrogate Loss Functions and the Scoring Function ClassMingyuan Zhang, Shivani Agarwal 0001. [doi]
• Stochasticity of Deterministic Gradient Descent: Large Learning Rate for Multiscale Objective FunctionLingkai Kong, Molei Tao. [doi]
• Adversarial Soft Advantage Fitting: Imitation Learning without Policy OptimizationPaul Barde, Julien Roy, Wonseok Jeon, Joelle Pineau, Chris Pal, Derek Nowrouzezahrai. [doi]
• Forget About the LiDAR: Self-Supervised Depth Estimators with MED Probability VolumesJuan Luis Gonzalez Bello, Munchurl Kim. [doi]
• Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-SolversKiwon Um, Robert Brand, Yun (Raymond) Fei, Philipp Holl, Nils Thuerey. [doi]
• CompRess: Self-Supervised Learning by Compressing RepresentationsSoroush Abbasi Koohpayegani, Ajinkya Tejankar, Hamed Pirsiavash. [doi]
• Neural Complexity MeasuresYoonho Lee, Juho Lee, Sung Ju Hwang, Eunho Yang, Seungjin Choi. [doi]
• Learning Black-Box Attackers with Transferable Priors and Query FeedbackJiancheng Yang, Yangzhou Jiang, Xiaoyang Huang, Bingbing Ni, Chenglong Zhao. [doi]
• Do Adversarially Robust ImageNet Models Transfer Better?Hadi Salman, Andrew Ilyas, Logan Engstrom, Ashish Kapoor, Aleksander Madry. [doi]
• Strictly Batch Imitation Learning by Energy-based Distribution MatchingDaniel Jarrett, Ioana Bica, Mihaela van der Schaar. [doi]
• Influence-Augmented Online Planning for Complex EnvironmentsJinke He, Miguel Suau, Frans A. Oliehoek. [doi]
• What Neural Networks Memorize and Why: Discovering the Long Tail via Influence EstimationVitaly Feldman, Chiyuan Zhang. [doi]
• Hierarchical Neural Architecture Search for Deep Stereo MatchingXuelian Cheng, Yiran Zhong, Mehrtash Harandi, Yuchao Dai, Xiaojun Chang, Hongdong Li, Tom Drummond, ZongYuan Ge. [doi]
• Incorporating Interpretable Output Constraints in Bayesian Neural NetworksWanqian Yang, Lars Lorch, Moritz A. Graule, Himabindu Lakkaraju, Finale Doshi-Velez. [doi]
• Correlation Robust Influence MaximizationLouis Chen, Divya Padmanabhan, Chee Chin Lim, Karthik Natarajan. [doi]
• Probabilistic Orientation Estimation with Matrix Fisher DistributionsDavid Mohlin, Josephine Sullivan, Gérald Bianchi. [doi]
• Adversarial Robustness of Supervised Sparse CodingJeremias Sulam, Ramchandran Muthukumar, Raman Arora. [doi]
• Multi-Stage Influence FunctionHongge Chen, Si Si, Yang Li 0058, Ciprian Chelba, Sanjiv Kumar, Duane S. Boning, Cho-Jui Hsieh. [doi]
• Hausdorff Dimension, Heavy Tails, and Generalization in Neural NetworksUmut Simsekli, Ozan Sener, George Deligiannidis, Murat A. Erdogdu. [doi]
• Effective Diversity in Population Based Reinforcement LearningJack Parker-Holder, Aldo Pacchiano, Krzysztof Marcin Choromanski, Stephen J. Roberts. [doi]
• Deep reconstruction of strange attractors from time seriesWilliam Gilpin. [doi]
• Sub-sampling for Efficient Non-Parametric Bandit ExplorationDorian Baudry, Emilie Kaufmann, Odalric-Ambrym Maillard. [doi]
• Robust Multi-Agent Reinforcement Learning with Model UncertaintyKaiqing Zhang, Tao Sun, Yunzhe Tao, Sahika Genc, Sunil Mallya, Tamer Basar. [doi]
• Minibatch Stochastic Approximate Proximal Point MethodsHilal Asi, Karan Chadha, Gary Cheng, John C. Duchi. [doi]
• Neural Mesh Flow: 3D Manifold Mesh Generation via Diffeomorphic FlowsKunal Gupta, Manmohan Chandraker. [doi]
• From Boltzmann Machines to Neural Networks and Back AgainSurbhi Goel, Adam R. Klivans, Frederic Koehler. [doi]
• Is Long Horizon RL More Difficult Than Short Horizon RL?Ruosong Wang, Simon S. Du, Lin F. Yang, Sham M. Kakade. [doi]
• High-Dimensional Bayesian Optimization via Nested Riemannian ManifoldsNoémie Jaquier, Leonel Dario Rozo. [doi]
• Hybrid Variance-Reduced SGD Algorithms For Minimax Problems with Nonconvex-Linear FunctionQuoc Tran-Dinh, Deyi Liu, Lam Nguyen. [doi]
• Distributionally Robust Parametric Maximum Likelihood EstimationViet Anh Nguyen, Xuhui Zhang, José H. Blanchet, Angelos Georghiou. [doi]
• How to Characterize The Landscape of Overparameterized Convolutional Neural NetworksYihong Gu, Weizhong Zhang, Cong Fang, Jason D. Lee, Tong Zhang 0001. [doi]
• Crush Optimism with Pessimism: Structured Bandits Beyond Asymptotic OptimalityKwang-Sung Jun, Chicheng Zhang. [doi]
• Sufficient dimension reduction for classification using principal optimal transport directionCheng Meng, Jun Yu, Jingyi Zhang, Ping Ma, Wenxuan Zhong. [doi]
• DynaBERT: Dynamic BERT with Adaptive Width and DepthLu Hou, Zhiqi Huang, Lifeng Shang, Xin Jiang, Xiao Chen, Qun Liu. [doi]
• Towards Better Generalization of Adaptive Gradient MethodsYingxue Zhou, Belhal Karimi, Jinxing Yu, Zhiqiang Xu, Ping Li 0001. [doi]
• Learning identifiable and interpretable latent models of high-dimensional neural activity using pi-VAEDing Zhou, Xue-Xin Wei. [doi]
• Bayesian Robust Optimization for Imitation LearningDaniel S. Brown, Scott Niekum, Marek Petrik. [doi]
• Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in RegretYingjie Fei, Zhuoran Yang, Yudong Chen, Zhaoran Wang, Qiaomin Xie. [doi]
• Identifying Learning Rules From Neural Network ObservablesAran Nayebi, Sanjana Srivastava, Surya Ganguli, Daniel L. Yamins. [doi]
• Certified Monotonic Neural NetworksXingchao Liu, Xing Han, Na Zhang, Qiang Liu 0001. [doi]
• Memory Based Trajectory-conditioned Policies for Learning from Sparse RewardsYijie Guo, Jongwook Choi, Marcin Moczulski, Shengyu Feng, Samy Bengio, Mohammad Norouzi 0002, Honglak Lee. [doi]
• Towards Playing Full MOBA Games with Deep Reinforcement LearningDeheng Ye, Guibin Chen, Wen Zhang, Sheng Chen, Bo Yuan, Bo Liu, Jia Chen, Zhao Liu, Fuhao Qiu, Hongsheng Yu, Yinyuting Yin, Bei Shi, Liang Wang, Tengfei Shi, Qiang Fu, Wei Yang, Lanxiao Huang, Wei Liu. [doi]
• Experimental design for MRI by greedy policy searchTim Bakker, Herke van Hoof, Max Welling. [doi]
• Bayesian Bits: Unifying Quantization and PruningMart van Baalen, Christos Louizos, Markus Nagel, Rana Ali Amjad, Ying Wang, Tijmen Blankevoort, Max Welling. [doi]
• RANet: Region Attention Network for Semantic SegmentationDingguo Shen, Yuanfeng Ji, Ping Li, Yi Wang, Di Lin. [doi]
• Fast Transformers with Clustered AttentionApoorv Vyas, Angelos Katharopoulos, François Fleuret. [doi]
• Overfitting Can Be Harmless for Basis Pursuit, But Only to a DegreePeizhong Ju, Xiaojun Lin, Jia Liu 0002. [doi]
• Dialog without Dialog Data: Learning Visual Dialog Agents from VQA DataMichael Cogswell, Jiasen Lu, Rishabh Jain, Stefan Lee, Devi Parikh, Dhruv Batra. [doi]
• Graph Policy Network for Transferable Active Learning on GraphsShengding Hu, Zheng Xiong, Meng Qu, Xingdi Yuan, Marc-Alexandre Côté, Zhiyuan Liu 0001, Jian Tang. [doi]
• 3D Shape Reconstruction from Vision and TouchEdward J. Smith, Roberto Calandra, Adriana Romero, Georgia Gkioxari, David Meger, Jitendra Malik, Michal Drozdzal. [doi]
• Shared Space Transfer Learning for analyzing multi-site fMRI dataMuhammad Yousefnezhad, Alessandro Selvitella, Daoqiang Zhang, Andrew J. Greenshaw, Russell Greiner. [doi]
• Multi-Robot Collision Avoidance under Uncertainty with Probabilistic Safety Barrier CertificatesWenhao Luo, Wen Sun, Ashish Kapoor. [doi]
• Leverage the Average: an Analysis of KL Regularization in Reinforcement LearningNino Vieillard, Tadashi Kozuno, Bruno Scherrer, Olivier Pietquin, Rémi Munos, Matthieu Geist. [doi]
• FixMatch: Simplifying Semi-Supervised Learning with Consistency and ConfidenceKihyuk Sohn, David Berthelot, Nicholas Carlini, Zizhao Zhang, Han Zhang, Colin Raffel, Ekin Dogus Cubuk, Alexey Kurakin, Chun-Liang Li. [doi]
• A Statistical Framework for Low-bitwidth Training of Deep Neural NetworksJianfei Chen, Yu Gai, Zhewei Yao, Michael W. Mahoney, Joseph E. Gonzalez. [doi]
• An analytic theory of shallow networks dynamics for hinge loss classificationFranco Pellegrini, Giulio Biroli. [doi]
• Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image PerturbationsJoel Dapello, Tiago Marques, Martin Schrimpf, Franziska Geiger, David D. Cox, James J. DiCarlo. [doi]
• Self-Supervised Learning by Cross-Modal Audio-Video ClusteringHumam Alwassel, Dhruv Mahajan 0001, Bruno Korbar, Lorenzo Torresani, Bernard Ghanem, Du Tran. [doi]
• GramGAN: Deep 3D Texture Synthesis From 2D ExemplarsTiziano Portenier, Siavash Arjomand Bigdeli, Orcun Goksel. [doi]
• A novel variational form of the Schatten-$p$ quasi-normParis Giampouras, René Vidal, Athanasios A. Rontogiannis, Benjamin D. Haeffele. [doi]
• Parameterized Explainer for Graph Neural NetworkDongsheng Luo, Wei Cheng, Dongkuan Xu, Wenchao Yu, Bo Zong, Haifeng Chen, Xiang Zhang 0001. [doi]
• CaSPR: Learning Canonical Spatiotemporal Point Cloud RepresentationsDavis Rempe, Tolga Birdal, Yongheng Zhao, Zan Gojcic, Srinath Sridhar 0002, Leonidas J. Guibas. [doi]
• Projection Robust Wasserstein Distance and Riemannian OptimizationTianyi Lin, Chenyou Fan, Nhat Ho, Marco Cuturi, Michael I. Jordan. [doi]
• Improved Schemes for Episodic Memory-based Lifelong LearningYunhui Guo, Mingrui Liu, Tianbao Yang, Tajana Rosing. [doi]
• Spin-Weighted Spherical CNNsCarlos Esteves, Ameesh Makadia, Kostas Daniilidis. [doi]
• Pruning Filter in FilterFanxu Meng, Hao Cheng, Ke Li, Huixiang Luo, Xiaowei Guo, Guangming Lu, Xing Sun. [doi]
• First Order Constrained Optimization in Policy SpaceYiming Zhang 0010, Quan Vuong, Keith W. Ross. [doi]
• On the Stability and Convergence of Robust Adversarial Reinforcement Learning: A Case Study on Linear Quadratic SystemsKaiqing Zhang, Bin Hu, Tamer Basar. [doi]
• Learning Linear Programs from Optimal DecisionsYingcong Tan, Daria Terekhov, Andrew Delong. [doi]
• Stage-wise Conservative Linear BanditsAhmadreza Moradipari, Christos Thrampoulidis, Mahnoosh Alizadeh. [doi]
• Estimating weighted areas under the ROC curveAndreas Maurer, Massimiliano Pontil. [doi]
• Graph Stochastic Neural Networks for Semi-supervised LearningHaibo Wang, Chuan Zhou 0001, Xin Chen, Jia Wu 0001, Shirui Pan, Jilong Wang. [doi]
• Kernel Based Progressive Distillation for Adder Neural NetworksYixing Xu, Chang Xu 0002, Xinghao Chen 0001, Wei Zhang, Chunjing Xu, Yunhe Wang. [doi]
• Learning Individually Inferred Communication for Multi-Agent CooperationZiluo Ding, Tiejun Huang, Zongqing Lu. [doi]
• Implicit Rank-Minimizing AutoencoderLi Jing, Jure Zbontar, Yann LeCun. [doi]
• Towards Interpretable Natural Language Understanding with Explanations as Latent VariablesWangchunshu Zhou, Jinyi Hu, Hanlin Zhang, Xiaodan Liang, Maosong Sun, Chenyan Xiong, Jian Tang. [doi]
• Finding Second-Order Stationary Points Efficiently in Smooth Nonconvex Linearly Constrained Optimization ProblemsSongtao Lu, Meisam Razaviyayn, Bo Yang, Kejun Huang, Mingyi Hong. [doi]
• Ensemble Distillation for Robust Model Fusion in Federated LearningTao Lin, Lingjing Kong, Sebastian U. Stich, Martin Jaggi. [doi]
• Woodbury Transformations for Deep Generative FlowsYou Lu 0003, Bert Huang. [doi]
• Rethinking Importance Weighting for Deep Learning under Distribution ShiftTongtong Fang, Nan Lu, Gang Niu 0001, Masashi Sugiyama. [doi]
• Estimating Training Data Influence by Tracing Gradient DescentGarima Pruthi, Frederick Liu, Satyen Kale, Mukund Sundararajan. [doi]
• 3D Self-Supervised Methods for Medical ImagingAiham Taleb, Winfried Loetzsch, Noel Danz, Julius Severin, Thomas Gaertner, Benjamin Bergner, Christoph Lippert. [doi]
• Reciprocal Adversarial Learning via Characteristic FunctionsShengxi Li, Zeyang Yu, Min Xiang, Danilo P. Mandic. [doi]
• Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimizationBenjamin Aubin, Florent Krzakala, Yue M. Lu, Lenka Zdeborová. [doi]
• Regularizing Towards Permutation Invariance In Recurrent ModelsEdo Cohen-Karlik, Avichai Ben David, Amir Globerson. [doi]
• A General Method for Robust Learning from BatchesAyush Jain, Alon Orlitsky. [doi]
• Improving Auto-Augment via Augmentation-Wise Weight SharingKeyu Tian, Chen Lin, Ming Sun, Luping Zhou, Junjie Yan, Wanli Ouyang. [doi]
• Bridging Imagination and Reality for Model-Based Deep Reinforcement LearningGuangxiang Zhu, Minghao Zhang, Honglak Lee, Chongjie Zhang. [doi]
• HiPPO: Recurrent Memory with Optimal Polynomial ProjectionsAlbert Gu, Tri Dao, Stefano Ermon, Atri Rudra, Christopher Ré. [doi]
• Learning outside the Black-Box: The pursuit of interpretable modelsJonathan Crabbé, Yao Zhang, William R. Zame, Mihaela van der Schaar. [doi]
• No-regret Learning in Price Competitions under Consumer Reference EffectsNegin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang. [doi]
• ShapeFlow: Learnable Deformation Flows Among 3D ShapesChiyu Max Jiang, Jingwei Huang, Andrea Tagliasacchi, Leonidas J. Guibas. [doi]
• Geo-PIFu: Geometry and Pixel Aligned Implicit Functions for Single-view Human ReconstructionTong He, John P. Collomosse, Hailin Jin, Stefano Soatto. [doi]
• Coresets for Regressions with Panel DataLingxiao Huang, K. Sudhir, Nisheeth K. Vishnoi. [doi]
• Memory-Efficient Learning of Stable Linear Dynamical Systems for Prediction and ControlGiorgos Mamakoukas, Orest Xherija, Todd Murphey. [doi]
• Unsupervised Learning of Object Landmarks via Self-Training CorrespondenceDimitrios Mallis, Enrique Sanchez, Matthew Bell, Georgios Tzimiropoulos. [doi]
• Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural ProcessesAndrew Y. K. Foong, Wessel Bruinsma, Jonathan Gordon 0003, Yann Dubois, James Requeima, Richard E. Turner. [doi]
• Contextual Games: Multi-Agent Learning with Side InformationPier Giuseppe Sessa, Ilija Bogunovic, Andreas Krause 0001, Maryam Kamgarpour. [doi]
• Learning Disentangled Representations and Group Structure of Dynamical EnvironmentsRobin Quessard, Thomas D. Barrett, William R. Clements. [doi]
• Almost Optimal Model-Free Reinforcement Learningvia Reference-Advantage DecompositionZihan Zhang, Yuan Zhou 0007, Xiangyang Ji. [doi]
• Value-driven Hindsight ModellingArthur Guez, Fabio Viola, Theophane Weber, Lars Buesing, Steven Kapturowski, Doina Precup, David Silver, Nicolas Heess. [doi]
• Variational Policy Gradient Method for Reinforcement Learning with General UtilitiesJunyu Zhang, Alec Koppel, Amrit Singh Bedi, Csaba Szepesvári, Mengdi Wang. [doi]
• Large-Scale Adversarial Training for Vision-and-Language Representation LearningZhe Gan, Yen-Chun Chen 0001, Linjie Li, Chen Zhu, Yu Cheng 0001, Jingjing Liu 0001. [doi]
• Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for FreeHaotao Wang, Tianlong Chen, Shupeng Gui, Ting-Kuei Hu, Ji Liu 0002, Zhangyang Wang. [doi]
• Stochastic Optimization with Laggard Data PipelinesNaman Agarwal, Rohan Anil, Tomer Koren, Kunal Talwar, Cyril Zhang. [doi]
• Temporal Variability in Implicit Online LearningNicolò Campolongo, Francesco Orabona. [doi]
• Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution AlignmentBen Usman, Avneesh Sud, Nick Dufour, Kate Saenko. [doi]
• Learning Long-Term Dependencies in Irregularly-Sampled Time SeriesMathias Lechner, Ramin M. Hasani. [doi]
• Statistical and Topological Properties of Sliced Probability DivergencesKimia Nadjahi, Alain Durmus, Lénaïc Chizat, Soheil Kolouri, Shahin Shahrampour, Umut Simsekli. [doi]
• On the linearity of large non-linear models: when and why the tangent kernel is constantChaoyue Liu 0001, Libin Zhu, Mikhail Belkin. [doi]
• Hard Example Generation by Texture Synthesis for Cross-domain Shape Similarity LearningHuan Fu, Shunming Li, Rongfei Jia, Mingming Gong, Binqiang Zhao, Dacheng Tao. [doi]
• GCOMB: Learning Budget-constrained Combinatorial Algorithms over Billion-sized GraphsSahil Manchanda, Akash Mittal, Anuj Dhawan, Sourav Medya, Sayan Ranu, Ambuj Singh. [doi]
• A Benchmark for Systematic Generalization in Grounded Language UnderstandingLaura Ruis, Jacob Andreas, Marco Baroni, Diane Bouchacourt, Brenden M. Lake. [doi]
• Deep Multimodal Fusion by Channel ExchangingYikai Wang, Wenbing Huang, Fuchun Sun, Tingyang Xu, Yu Rong, JunZhou Huang. [doi]
• Improving robustness against common corruptions by covariate shift adaptationSteffen Schneider, Evgenia Rusak, Luisa Eck, Oliver Bringmann 0001, Wieland Brendel, Matthias Bethge. [doi]
• Robust-Adaptive Control of Linear Systems: beyond Quadratic CostsEdouard Leurent, Odalric-Ambrym Maillard, Denis V. Efimov. [doi]
• Adversarial Counterfactual Learning and Evaluation for Recommender SystemDa Xu, Chuanwei Ruan, Evren Körpeoglu, Sushant Kumar, Kannan Achan. [doi]
• Gradient Regularized V-Learning for Dynamic Treatment RegimesYao Zhang, Mihaela van der Schaar. [doi]
• Provably Consistent Partial-Label LearningLei Feng, Jiaqi Lv, Bo Han 0003, Miao Xu, Gang Niu 0001, Xin Geng, Bo An 0001, Masashi Sugiyama. [doi]
• Part-dependent Label Noise: Towards Instance-dependent Label NoiseXiaobo Xia, Tongliang Liu, Bo Han 0003, Nannan Wang, Mingming Gong, Haifeng Liu, Gang Niu 0001, Dacheng Tao, Masashi Sugiyama. [doi]
• Graphon Neural Networks and the Transferability of Graph Neural NetworksLuana Ruiz, Luiz F. O. Chamon, Alejandro Ribeiro. [doi]
• Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEsJianzhun Du, Joseph Futoma, Finale Doshi-Velez. [doi]
• Characterizing Optimal Mixed Policies: Where to Intervene and What to ObserveSanghack Lee, Elias Bareinboim. [doi]
• Pipeline PSRO: A Scalable Approach for Finding Approximate Nash Equilibria in Large GamesStephen McAleer, John B. Lanier, Roy Fox, Pierre Baldi. [doi]
• Path Sample-Analytic Gradient Estimators for Stochastic Binary NetworksAlexander Shekhovtsov, Viktor Yanush, Boris Flach. [doi]
• Random Reshuffling: Simple Analysis with Vast ImprovementsKonstantin Mishchenko, Ahmed Khaled Ragab Bayoumi, Peter Richtárik. [doi]
• TinyTL: Reduce Memory, Not Parameters for Efficient On-Device LearningHan Cai, Chuang Gan, Ligeng Zhu, Song Han 0003. [doi]
• Removing Bias in Multi-modal Classifiers: Regularization by Maximizing Functional EntropiesItai Gat, Idan Schwartz, Alexander G. Schwing, Tamir Hazan. [doi]
• POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic AnalysisWeichao Mao, Kaiqing Zhang, Qiaomin Xie, Tamer Basar. [doi]
• GOCor: Bringing Globally Optimized Correspondence Volumes into Your Neural NetworkPrune Truong, Martin Danelljan, Luc Van Gool, Radu Timofte. [doi]
• All-or-nothing statistical and computational phase transitions in sparse spiked matrix estimationJean Barbier, Nicolas Macris, Cynthia Rush. [doi]
• Hierarchical nucleation in deep neural networksDiego Doimo, Aldo Glielmo, Alessio Ansuini, Alessandro Laio. [doi]
• GPS-Net: Graph-based Photometric Stereo NetworkZhuokun Yao, Kun Li, Ying Fu, Haofeng Hu, Boxin Shi. [doi]
• Statistical Efficiency of Thompson Sampling for Combinatorial Semi-BanditsPierre Perrault, Etienne Boursier, Michal Valko, Vianney Perchet. [doi]
• A Convolutional Auto-Encoder for Haplotype Assembly and Viral Quasispecies ReconstructionZiqi Ke, Haris Vikalo. [doi]
• Model Interpretability through the lens of Computational ComplexityPablo Barceló, Mikaël Monet, Jorge Pérez 0001, Bernardo Subercaseaux. [doi]
• BanditPAM: Almost Linear Time k-Medoids Clustering via Multi-Armed BanditsMo Tiwari, Martin Jinye Zhang, James Mayclin, Sebastian Thrun, Chris Piech, Ilan Shomorony. [doi]
• High-Dimensional Sparse Linear BanditsBotao Hao, Tor Lattimore, Mengdi Wang. [doi]
• Improved Techniques for Training Score-Based Generative ModelsYang Song 0011, Stefano Ermon. [doi]
• Instance Selection for GANsTerrance Devries, Michal Drozdzal, Graham W. Taylor. [doi]
• COPT: Coordinated Optimal Transport on GraphsYihe Dong, Will Sawin. [doi]
• On the equivalence of molecular graph convolution and molecular wave function with poor basis setMasashi Tsubaki, Teruyasu Mizoguchi. [doi]
• Chaos, Extremism and Optimism: Volume Analysis of Learning in GamesYun Kuen Cheung, Georgios Piliouras. [doi]
• Second Order Optimality in Decentralized Non-Convex Optimization via Perturbed Gradient TrackingIsidoros Tziotis, Constantine Caramanis, Aryan Mokhtari. [doi]
• The Hateful Memes Challenge: Detecting Hate Speech in Multimodal MemesDouwe Kiela, Hamed Firooz, Aravind Mohan, Vedanuj Goswami, Amanpreet Singh, Pratik Ringshia, Davide Testuggine. [doi]
• Generalized BoostingArun Sai Suggala, Bingbin Liu, Pradeep Ravikumar. [doi]
• Kernel Methods Through the Roof: Handling Billions of Points EfficientlyGiacomo Meanti, Luigi Carratino, Lorenzo Rosasco, Alessandro Rudi. [doi]
• Applications of Common Entropy for Causal InferenceMurat Kocaoglu, Sanjay Shakkottai, Alexandros G. Dimakis, Constantine Caramanis, Sriram Vishwanath. [doi]
• Towards Theoretically Understanding Why Sgd Generalizes Better Than Adam in Deep LearningPan Zhou, Jiashi Feng, Chao Ma 0012, Caiming Xiong, Steven Chu Hong Hoi, Weinan E. [doi]
• Prophet Attention: Predicting Attention with Future AttentionFenglin Liu, Xuancheng Ren, Xian Wu, Shen Ge, Wei Fan 0001, Yuexian Zou, Xu Sun 0001. [doi]
• Exchangeable Neural ODE for Set ModelingYang Li 0012, Haidong Yi, Christopher M. Bender, Siyuan Shan, Junier B. Oliva. [doi]
• Feature Importance Ranking for Deep LearningMaksymilian Wojtas, Ke Chen 0001. [doi]
• Factor Graph Neural NetworksZhen Zhang, Fan Wu, Wee Sun Lee. [doi]
• A new convergent variant of Q-learning with linear function approximationDiogo Carvalho, Francisco S. Melo, Pedro Santos 0001. [doi]
• Inference for Batched BanditsKelly W. Zhang, Lucas Janson, Susan A. Murphy. [doi]
• PIE-NET: Parametric Inference of Point Cloud EdgesXiaogang Wang 0005, Yuelang Xu, Kai Xu 0004, Andrea Tagliasacchi, Bin Zhou, Ali Mahdavi-Amiri, Hao Zhang 0002. [doi]
• Making Non-Stochastic Control (Almost) as Easy as StochasticMax Simchowitz. [doi]
• Object Goal Navigation using Goal-Oriented Semantic ExplorationDevendra Singh Chaplot, Dhiraj Gandhi, Abhinav Gupta 0001, Russ R. Salakhutdinov. [doi]
• Fully Convolutional Mesh Autoencoder using Efficient Spatially Varying KernelsYi Zhou, Chenglei Wu, Zimo Li, Chen Cao, Yuting Ye, Jason M. Saragih, Hao Li, Yaser Sheikh. [doi]
• Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample ComplexityKaiqing Zhang, Sham M. Kakade, Tamer Basar, Lin F. Yang. [doi]
• Neural Unsigned Distance Fields for Implicit Function LearningJulian Chibane, Aymen Mir, Gerard Pons-Moll. [doi]
• Online Sinkhorn: Optimal Transport distances from sample streamsArthur Mensch, Gabriel Peyré. [doi]
• Sampling-Decomposable Generative Adversarial RecommenderBinbin Jin, Defu Lian, Zheng Liu, Qi Liu 0003, Jianhui Ma, Xing Xie 0001, Enhong Chen. [doi]
• HM-ANN: Efficient Billion-Point Nearest Neighbor Search on Heterogeneous MemoryJie Ren 0015, Minjia Zhang, Dong Li. [doi]
• Online Multitask Learning with Long-Term MemoryMark Herbster, Stephen Pasteris, Lisa Tse. [doi]
• A Finite-Time Analysis of Two Time-Scale Actor-Critic MethodsYue Wu, Weitong Zhang, Pan Xu 0002, Quanquan Gu. [doi]
• Efficient Planning in Large MDPs with Weak Linear Function ApproximationRoshan Shariff, Csaba Szepesvári. [doi]
• Untangling tradeoffs between recurrence and self-attention in artificial neural networksGiancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal, Kyle Goyette, Yoshua Bengio, Guillaume Lajoie. [doi]
• Goal-directed Generation of Discrete Structures with Conditional Generative ModelsAmina Mollaysa, Brooks Paige, Alexandros Kalousis. [doi]
• Reinforcement Learning with Augmented DataMichael Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel, Aravind Srinivas. [doi]
• Fast geometric learning with symbolic matricesJean Feydy, Joan Alexis Glaunès, Benjamin Charlier, Michael M. Bronstein. [doi]
• Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous GNNsHao Tang, Zhiao Huang, Jiayuan Gu, Bao-Liang Lu, Hao Su 0001. [doi]
• Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? - A Neural Tangent Kernel PerspectiveKaixuan Huang, Yuqing Wang, Molei Tao, Tuo Zhao. [doi]
• Revisiting Frank-Wolfe for Polytopes: Strict Complementarity and SparsityDan Garber. [doi]
• Predictive Information Accelerates Learning in RLKuang-Huei Lee, Ian Fischer, Anthony Liu, Yijie Guo, Honglak Lee, John Canny, Sergio Guadarrama. [doi]
• Learning to Approximate a Bregman DivergenceAli Siahkamari, Xide Xia, Venkatesh Saligrama, David A. Castañón, Brian Kulis. [doi]
• The Surprising Simplicity of the Early-Time Learning Dynamics of Neural NetworksWei Hu, Lechao Xiao, Ben Adlam, Jeffrey Pennington. [doi]
• Auditing Differentially Private Machine Learning: How Private is Private SGD?Matthew Jagielski, Jonathan R. Ullman, Alina Oprea. [doi]
• Online Neural Connectivity Estimation with Noisy Group TestingAnne Draelos, John M. Pearson. [doi]
• Curriculum learning for multilevel budgeted combinatorial problemsAdel Nabli, Margarida Carvalho. [doi]
• Learning Agent Representations for Ice HockeyGuiliang Liu, Oliver Schulte, Pascal Poupart, Mike Rudd, Mehrsan Javan. [doi]
• Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable RecoursesKaivalya Rawal, Himabindu Lakkaraju. [doi]
• Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node EmbeddingsYu Chen 0022, Lingfei Wu, Mohammed J. Zaki. [doi]
• Implicit Neural Representations with Periodic Activation FunctionsVincent Sitzmann, Julien N. P. Martel, Alexander W. Bergman, David B. Lindell, Gordon Wetzstein. [doi]
• Task-Oriented Feature DistillationLinfeng Zhang, Yukang Shi, Zuoqiang Shi, Kaisheng Ma, Chenglong Bao. [doi]
• Efficient Low Rank Gaussian Variational Inference for Neural NetworksMarcin Tomczak, Siddharth Swaroop, Richard E. Turner. [doi]
• TorsionNet: A Reinforcement Learning Approach to Sequential Conformer SearchTarun Gogineni, Ziping Xu, Exequiel Punzalan, Runxuan Jiang, Joshua Kammeraad, Ambuj Tewari, Paul Zimmerman. [doi]
• Entropic Optimal Transport between Unbalanced Gaussian Measures has a Closed FormHicham Janati, Boris Muzellec, Gabriel Peyré, Marco Cuturi. [doi]
• What Did You Think Would Happen? Explaining Agent Behaviour through Intended OutcomesHerman Yau, Chris Russell 0001, Simon Hadfield. [doi]
• Quantifying the Empirical Wasserstein Distance to a Set of Measures: Beating the Curse of DimensionalityNian Si, Jose H. Blanchet, Soumyadip Ghosh, Mark S. Squillante. [doi]
• Automatic Curriculum Learning through Value DisagreementYunzhi Zhang, Pieter Abbeel, Lerrel Pinto. [doi]
• Dynamic Submodular MaximizationMorteza Monemizadeh. [doi]
• A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game EncodingBruno Lecouat, Jean Ponce, Julien Mairal. [doi]
• MCUNet: Tiny Deep Learning on IoT DevicesJi Lin, Wei-Ming Chen, Yujun Lin, John Cohn, Chuang Gan, Song Han 0003. [doi]
• PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient LearningAlekh Agarwal, Mikael Henaff, Sham M. Kakade, Wen Sun. [doi]
• Robustness of Bayesian Neural Networks to Gradient-Based AttacksGinevra Carbone, Matthew Wicker, Luca Laurenti, Andrea Patané, Luca Bortolussi, Guido Sanguinetti. [doi]
• Efficient Clustering Based On A Unified View Of $K$-means And Ratio-cutShenfei Pei, Feiping Nie 0001, Rong Wang, Xuelong Li. [doi]
• SMYRF - Efficient Attention using Asymmetric ClusteringGiannis Daras, Nikita Kitaev, Augustus Odena, Alexandros G. Dimakis. [doi]
• Online Robust Regression via SGD on the l1 lossScott Pesme, Nicolas Flammarion. [doi]
• Adaptation Properties Allow Identification of Optimized Neural CodesLuke I. Rast, Jan Drugowitsch. [doi]
• Almost Surely Stable Deep DynamicsNathan P. Lawrence, Philip D. Loewen, Michael G. Forbes, Johan U. Backström, R. Bhushan Gopaluni. [doi]
• Mitigating Forgetting in Online Continual Learning via Instance-Aware ParameterizationHung-Jen Chen, An-Chieh Cheng, Da-Cheng Juan, Wei Wei 0025, Min Sun. [doi]
• Multimodal Graph Networks for Compositional Generalization in Visual Question AnsweringRaeid Saqur, Karthik Narasimhan. [doi]
• Multi-task Additive Models for Robust Estimation and Automatic Structure DiscoveryYingjie Wang, Hong Chen, Feng Zheng, Chen Xu, Tieliang Gong, Yanhong Chen. [doi]
• Stable and expressive recurrent vision modelsDrew Linsley, Alekh Karkada Ashok, Lakshmi Narasimhan Govindarajan, Rex Liu, Thomas Serre. [doi]
• Self-Imitation Learning via Generalized Lower Bound Q-learningYunhao Tang. [doi]
• DeepSVG: A Hierarchical Generative Network for Vector Graphics AnimationAlexandre Carlier, Martin Danelljan, Alexandre Alahi, Radu Timofte. [doi]
• CryptoNAS: Private Inference on a ReLU BudgetZahra Ghodsi, Akshaj Kumar Veldanda, Brandon Reagen, Siddharth Garg. [doi]
• Residual Force Control for Agile Human Behavior Imitation and Extended Motion SynthesisYe Yuan 0007, Kris Kitani. [doi]
• Label-Aware Neural Tangent Kernel: Toward Better Generalization and Local ElasticityShuxiao Chen, Hangfeng He, Weijie J. Su. [doi]
• Fourier Spectrum Discrepancies in Deep Network Generated ImagesTarik Dzanic, Karan Shah, Freddie D. Witherden. [doi]
• Predicting Training Time Without TrainingLuca Zancato, Alessandro Achille, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto. [doi]
• Coresets for Near-Convex FunctionsMurad Tukan, Alaa Maalouf, Dan Feldman. [doi]
• Improved Algorithms for Convex-Concave Minimax OptimizationYuanhao Wang, Jian Li. [doi]
• Toward the Fundamental Limits of Imitation LearningNived Rajaraman, Lin F. Yang, Jiantao Jiao, Kannan Ramchandran. [doi]
• SGD with shuffling: optimal rates without component convexity and large epoch requirementsKwangjun Ahn, Chulhee Yun, Suvrit Sra. [doi]
• ImpatientCapsAndRuns: Approximately Optimal Algorithm Configuration from an Infinite PoolGellért Weisz, András György 0001, Wei-I Lin, Devon R. Graham, Kevin Leyton-Brown, Csaba Szepesvári, Brendan Lucier. [doi]
• Generative View Synthesis: From Single-view Semantics to Novel-view ImagesTewodros Amberbir Habtegebrial, Varun Jampani, Orazio Gallo, Didier Stricker. [doi]
• Online Decision Based Visual Tracking via Reinforcement LearningKe Song, Wei Zhang 0066, Ran Song, Yibin Li. [doi]
• Online MAP Inference of Determinantal Point ProcessesAditya Bhaskara, Amin Karbasi, Silvio Lattanzi, Morteza Zadimoghaddam. [doi]
• Pushing the Limits of Narrow Precision Inferencing at Cloud Scale with Microsoft Floating PointBita Darvish Rouhani, Daniel Lo, Ritchie Zhao, Ming Liu, Jeremy Fowers, Kalin Ovtcharov, Anna Vinogradsky, Sarah Massengill, Lita Yang, Ray Bittner, Alessandro Forin, Haishan Zhu, Taesik Na, Prerak Patel, Shuai Che, Lok Chand Koppaka, Xia Song, Subhojit Som, Kaustav Das, Saurabh T., Steven K. Reinhardt, Sitaram Lanka, Eric S. Chung, Doug Burger. [doi]
• Interpretable and Personalized Apprenticeship Scheduling: Learning Interpretable Scheduling Policies from Heterogeneous User DemonstrationsRohan R. Paleja, Andrew Silva, Letian Chen, Matthew C. Gombolay. [doi]
• Weak Form Generalized Hamiltonian LearningKevin Course, Trefor W. Evans, Prasanth B. Nair. [doi]
• Pre-training via ParaphrasingMike Lewis, Marjan Ghazvininejad, Gargi Ghosh, Armen Aghajanyan, Sida Wang, Luke Zettlemoyer. [doi]
• Robust Multi-Object Matching via Iterative Reweighting of the Graph Connection LaplacianYunpeng Shi, Shaohan Li, Gilad Lerman. [doi]
• On Uniform Convergence and Low-Norm Interpolation LearningLijia Zhou, D. J. Sutherland, Nati Srebro. [doi]
• Softmax Deep Double Deterministic Policy GradientsLing Pan, Qingpeng Cai, Longbo Huang. [doi]
• Low Distortion Block-Resampling with Spatially Stochastic NetworksSarah Jane Hong, Martín Arjovsky, Darryl Barnhart, Ian Thompson. [doi]
• A Non-Asymptotic Analysis for Stein Variational Gradient DescentAnna Korba, Adil Salim, Michael Arbel, Giulia Luise, Arthur Gretton. [doi]
• Deep Imitation Learning for Bimanual Robotic ManipulationFan Xie 0005, Alexander Chowdhury, M. Clara De Paolis Kaluza, Linfeng Zhao, Lawson L. S. Wong, Rose Yu. [doi]
• Community detection using fast low-cardinality semidefinite programming
Po-Wei Wang, J. Zico Kolter. [doi]
• Neural Dynamic Policies for End-to-End Sensorimotor LearningShikhar Bahl, Mustafa Mukadam, Abhinav Gupta 0001, Deepak Pathak. [doi]
• Finite Versus Infinite Neural Networks: an Empirical StudyJaehoon Lee, Samuel S. Schoenholz, Jeffrey Pennington, Ben Adlam, Lechao Xiao, Roman Novak, Jascha Sohl-Dickstein. [doi]
• Analytical Probability Distributions and Exact Expectation-Maximization for Deep Generative NetworksRandall Balestriero, Sebastien Paris, Richard G. Baraniuk. [doi]
• Subgraph Neural NetworksEmily Alsentzer, Samuel G. Finlayson, Michelle M. Li, Marinka Zitnik. [doi]
• Global Convergence of Deep Networks with One Wide Layer Followed by Pyramidal TopologyQuynh Nguyen, Marco Mondelli. [doi]
• Learning Rich RankingsArjun Seshadri, Stephen Ragain, Johan Ugander. [doi]
• Reconsidering Generative Objectives For Counterfactual ReasoningDanni Lu, Chenyang Tao, Junya Chen, Fan Li, Feng Guo, Lawrence Carin. [doi]
• Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance AwarenessJeremiah Z. Liu, Zi Lin, Shreyas Padhy, Dustin Tran, Tania Bedrax-Weiss, Balaji Lakshminarayanan. [doi]
• Lightweight Generative Adversarial Networks for Text-Guided Image ManipulationBowen Li, Xiaojuan Qi, Philip H. S. Torr, Thomas Lukasiewicz. [doi]
• Noise2Same: Optimizing A Self-Supervised Bound for Image DenoisingYaochen Xie, Zhengyang Wang, Shuiwang Ji. [doi]
• Learning Implicit Credit Assignment for Cooperative Multi-Agent Reinforcement LearningMeng Zhou, Ziyu Liu, Pengwei Sui, Yixuan Li, Yuk Ying Chung. [doi]
• AutoBSS: An Efficient Algorithm for Block Stacking Style SearchYikang Zhang, Jian Zhang, Zhao Zhong. [doi]
• On the Expressiveness of Approximate Inference in Bayesian Neural NetworksAndrew Y. K. Foong, David R. Burt, Yingzhen Li, Richard E. Turner. [doi]
• Assessing SATNet's Ability to Solve the Symbol Grounding ProblemOscar Chang, Lampros Flokas, Hod Lipson, Michael Spranger. [doi]
• Robust compressed sensing using generative modelsAjil Jalal, Liu Liu, Alexandros G. Dimakis, Constantine Caramanis. [doi]
• Faster Wasserstein Distance Estimation with the Sinkhorn DivergenceLénaïc Chizat, Pierre Roussillon, Flavien Léger, François-Xavier Vialard, Gabriel Peyré. [doi]
• Wasserstein Distances for Stereo Disparity EstimationDivyansh Garg, Yan Wang 0051, Bharath Hariharan, Mark Campbell 0001, Kilian Q. Weinberger, Wei-Lun Chao. [doi]
• MESA: Boost Ensemble Imbalanced Learning with MEta-SAmplerZhining Liu 0002, Pengfei Wei, Jing Jiang 0002, Wei Cao, Jiang Bian 0002, Yi Chang 0001. [doi]
• Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved ConfoundingVictor Veitch, Anisha Zaveri. [doi]
• Coresets via Bilevel Optimization for Continual Learning and StreamingZalán Borsos, Mojmir Mutny, Andreas Krause 0001. [doi]
• Re-Examining Linear Embeddings for High-Dimensional Bayesian OptimizationBenjamin Letham, Roberto Calandra, Akshara Rai, Eytan Bakshy. [doi]
• Uncovering the Topology of Time-Varying fMRI Data using Cubical PersistenceBastian Rieck, Tristan Yates, Christian Bock, Karsten M. Borgwardt, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy. [doi]
• Polynomial-Time Computation of Optimal Correlated Equilibria in Two-Player Extensive-Form Games with Public Chance Moves and BeyondGabriele Farina, Tuomas Sandholm. [doi]
• Hierarchical Quantized AutoencodersWill Williams, Sam Ringer, Tom Ash, David MacLeod, Jamie Dougherty, John Hughes. [doi]
• Proximity Operator of the Matrix Perspective Function and its ApplicationsJoong-Ho Won. [doi]
• Diverse Image Captioning with Context-Object Split Latent SpacesShweta Mahajan, Stefan Roth 0001. [doi]
• A kernel test for quasi-independenceTamara Fernandez, Wenkai Xu, Marc Ditzhaus, Arthur Gretton. [doi]
• Adapting to Misspecification in Contextual BanditsDylan J. Foster, Claudio Gentile, Mehryar Mohri, Julian Zimmert. [doi]
• Matrix Inference and Estimation in Multi-Layer ModelsParthe Pandit, Mojtaba Sahraee-Ardakan, Sundeep Rangan, Philip Schniter, Alyson K. Fletcher. [doi]
• Generative Neurosymbolic MachinesJindong Jiang, Sungjin Ahn. [doi]
• Latent World Models For Intrinsically Motivated ExplorationAleksandr Ermolov, Nicu Sebe. [doi]
• Top-k Training of GANs: Improving GAN Performance by Throwing Away Bad SamplesSamarth Sinha, Zhengli Zhao, Anirudh Goyal, Colin Raffel, Augustus Odena. [doi]
• Model Selection in Contextual Stochastic Bandit ProblemsAldo Pacchiano, My Phan, Yasin Abbasi-Yadkori, Anup Rao 0002, Julian Zimmert, Tor Lattimore, Csaba Szepesvári. [doi]
• f-Divergence Variational InferenceNeng Wan, Dapeng Li, Naira Hovakimyan. [doi]
• Texture Interpolation for Probing Visual PerceptionJonathan Vacher, Aida Davila, Adam Kohn, Ruben Coen Cagli. [doi]
• Multi-label Contrastive Predictive CodingJiaming Song, Stefano Ermon. [doi]
• A game-theoretic analysis of networked system control for common-pool resource management using multi-agent reinforcement learningArnu Pretorius, Scott Cameron, Elan Van Biljon, Tom Makkink, Shahil Mawjee, Jeremy du Plessis, Jonathan Shock, Alexandre Laterre, Karim Beguir. [doi]
• Self-Supervised Relational Reasoning for Representation LearningMassimiliano Patacchiola, Amos J. Storkey. [doi]
• Neurosymbolic Transformers for Multi-Agent CommunicationJeevana Priya Inala, Yichen Yang 0008, James Paulos, Yewen Pu, Osbert Bastani, Vijay Kumar 0001, Martin Rinard, Armando Solar-Lezama. [doi]
• Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian ProcessesMengdi Xu, Wenhao Ding, Jiacheng Zhu, Zuxin Liu, Baiming Chen, Ding Zhao. [doi]
• What Do Neural Networks Learn When Trained With Random Labels?Hartmut Maennel, Ibrahim M. Alabdulmohsin, Ilya O. Tolstikhin, Robert J. N. Baldock, Olivier Bousquet, Sylvain Gelly, Daniel Keysers. [doi]
• A Maximum-Entropy Approach to Off-Policy Evaluation in Average-Reward MDPsNevena Lazic, Dong Yin, Mehrdad Farajtabar, Nir Levine, Dilan Görür, Chris Harris, Dale Schuurmans. [doi]
• Learning to search efficiently for causally near-optimal treatmentsSamuel Håkansson, Viktor Lindblom, Omer Gottesman, Fredrik D. Johansson. [doi]
• UCSG-NET- Unsupervised Discovering of Constructive Solid Geometry TreeKacper Kania, Maciej Zieba, Tomasz Kajdanowicz. [doi]
• Conservative Q-Learning for Offline Reinforcement LearningAviral Kumar, Aurick Zhou, George Tucker, Sergey Levine. [doi]
• Efficient semidefinite-programming-based inference for binary and multi-class MRFsChirag Pabbaraju, Po-Wei Wang, J. Zico Kolter. [doi]
• Stochastic Deep Gaussian Processes over GraphsNaiqi Li, Wenjie Li, Jifeng Sun, Yinghua Gao, Yong Jiang, Shu-Tao Xia. [doi]
• On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome ThemChen Liu, Mathieu Salzmann, Tao Lin, Ryota Tomioka, Sabine Süsstrunk. [doi]
• Consistent Structural Relation Learning for Zero-Shot SegmentationPeike Li, Yunchao Wei, Yi Yang 0001. [doi]
• Tree! I am no Tree! I am a low dimensional Hyperbolic EmbeddingRishi Sonthalia, Anna C. Gilbert. [doi]
• Differentiable Neural Architecture Search in Equivalent Space with Exploration EnhancementMiao Zhang, Huiqi Li, Shirui Pan, Xiaojun Chang, ZongYuan Ge, Steven W. Su. [doi]
• Learning from Positive and Unlabeled Data with Arbitrary Positive ShiftZayd Hammoudeh, Daniel Lowd. [doi]
• Human Parsing Based Texture Transfer from Single Image to 3D Human via Cross-View ConsistencyFang Zhao, ShengCai Liao, Kaihao Zhang, Ling Shao 0001. [doi]
• SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergenceSinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet. [doi]
• Decentralized Accelerated Proximal Gradient DescentHaishan Ye, Ziang Zhou, Luo Luo, Tong Zhang 0001. [doi]
• The Discrete Gaussian for Differential PrivacyClément L. Canonne, Gautam Kamath 0001, Thomas Steinke. [doi]
• Retrieval-Augmented Generation for Knowledge-Intensive NLP TasksPatrick S. H. Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel 0001, Douwe Kiela. [doi]
• Self-Supervised Relationship ProbingJiuxiang Gu, Jason Kuen, Shafiq R. Joty, Jianfei Cai 0001, Vlad I. Morariu, Handong Zhao, Tong Sun. [doi]
• Over-parameterized Adversarial Training: An Analysis Overcoming the Curse of DimensionalityYi Zhang, Orestis Plevrakis, Simon S. Du, Xingguo Li, Zhao Song 0002, Sanjeev Arora. [doi]
• Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized OptimizationDmitry Kovalev, Adil Salim, Peter Richtárik. [doi]
• Sinkhorn Natural Gradient for Generative ModelsZebang Shen, Zhenfu Wang, Alejandro Ribeiro, Hamed Hassani. [doi]
• Limits to Depth Efficiencies of Self-AttentionYoav Levine, Noam Wies, Or Sharir, Hofit Bata, Amnon Shashua. [doi]
• Modeling and Optimization Trade-off in Meta-learningKatelyn Gao, Ozan Sener. [doi]
• Building powerful and equivariant graph neural networks with structural message-passingClément Vignac, Andreas Loukas, Pascal Frossard. [doi]
• UnModNet: Learning to Unwrap a Modulo Image for High Dynamic Range ImagingChu Zhou, Hang Zhao, Jin Han, Chang Xu 0002, Chao Xu 0006, Tiejun Huang, Boxin Shi. [doi]
• Online Linear Optimization with Many HintsAditya Bhaskara, Ashok Cutkosky, Ravi Kumar 0001, Manish Purohit. [doi]
• On Convergence of Nearest Neighbor Classifiers over Feature TransformationsLuka Rimanic, Cédric Renggli, Bo Li 0026, Ce Zhang. [doi]
• Network size and size of the weights in memorization with two-layers neural networksSébastien Bubeck, Ronen Eldan, Yin Tat Lee, Dan Mikulincer. [doi]
• A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max ProblemsJiawei Zhang, Peijun Xiao, Ruoyu Sun 0001, Zhi-Quan Luo. [doi]
• MMA Regularization: Decorrelating Weights of Neural Networks by Maximizing the Minimal AnglesZhennan Wang, Canqun Xiang, Wenbin Zou, Chen Xu 0004. [doi]
• Factorizable Graph Convolutional NetworksYiding Yang, Zunlei Feng, Mingli Song, Xinchao Wang. [doi]
• Provable Overlapping Community Detection in Weighted GraphsJimit Majmudar, Stephen A. Vavasis. [doi]
• Improving GAN Training with Probability Ratio Clipping and Sample ReweightingYue Wu, Pan Zhou, Andrew Gordon Wilson, Eric P. Xing, Zhiting Hu. [doi]
• PAC-Bayesian Bound for the Conditional Value at RiskZakaria Mhammedi, Benjamin Guedj, Robert C. Williamson. [doi]
• A Self-Tuning Actor-Critic AlgorithmTom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh. [doi]
• Provably adaptive reinforcement learning in metric spacesTongyi Cao, Akshay Krishnamurthy. [doi]
• f-GAIL: Learning f-Divergence for Generative Adversarial Imitation LearningXin Zhang, Yanhua Li, Ziming Zhang, Zhi-Li Zhang. [doi]
• Unsupervised Joint k-node Graph Representations with Compositional Energy-Based ModelsLeonardo Cotta, Carlos H. C. Teixeira, Ananthram Swami, Bruno Ribeiro 0001. [doi]
• Hierarchical Poset Decoding for Compositional Generalization in LanguageYinuo Guo, Zeqi Lin, Jian-Guang Lou, Dongmei Zhang. [doi]
• Supermasks in SuperpositionMitchell Wortsman, Vivek Ramanujan, Rosanne Liu, Aniruddha Kembhavi, Mohammad Rastegari, Jason Yosinski, Ali Farhadi. [doi]
• Causal Discovery from Soft Interventions with Unknown Targets: Characterization and LearningAmin Jaber, Murat Kocaoglu, Karthikeyan Shanmugam, Elias Bareinboim. [doi]
• SIRI: Spatial Relation Induced Network For Spatial Description ResolutionPeiyao Wang, Weixin Luo, Yanyu Xu, Haojie Li, Shugong Xu, Jianyu Yang, Shenghua Gao. [doi]
• OTLDA: A Geometry-aware Optimal Transport Approach for Topic ModelingViet Huynh, He Zhao, Dinh Phung 0001. [doi]
• Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning ApproachAlireza Fallah 0001, Aryan Mokhtari, Asuman E. Ozdaglar. [doi]
• Reinforcement Learning in Factored MDPs: Oracle-Efficient Algorithms and Tighter Regret Bounds for the Non-Episodic SettingZiping Xu, Ambuj Tewari. [doi]
• A Discrete Variational Recurrent Topic Model without the Reparametrization TrickMehdi Rezaee, Francis Ferraro. [doi]
• Scalable Belief Propagation via Relaxed SchedulingVitalii Aksenov, Dan Alistarh, Janne H. Korhonen. [doi]
• Spectra of the Conjugate Kernel and Neural Tangent Kernel for linear-width neural networksZhou Fan, Zhichao Wang. [doi]
• Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and ControlYaofeng Desmond Zhong, Naomi Ehrich Leonard. [doi]
• Learning to Execute Programs with Instruction Pointer Attention Graph Neural NetworksDavid Bieber, Charles Sutton, Hugo Larochelle, Daniel Tarlow. [doi]
• Understanding spiking networks through convex optimizationAllan Mancoo, Sander W. Keemink, Christian K. Machens. [doi]
• RELATE: Physically Plausible Multi-Object Scene Synthesis Using Structured Latent SpacesSébastien Ehrhardt, Oliver Groth, Aron Monszpart, Martin Engelcke, Ingmar Posner, Niloy J. Mitra, Andrea Vedaldi. [doi]
• Boosting Adversarial Training with Hypersphere EmbeddingTianyu Pang, Xiao Yang, Yinpeng Dong, Taufik Xu, Jun Zhu 0001, Hang Su 0006. [doi]
• On the Value of Out-of-Distribution Testing: An Example of Goodhart's LawDamien Teney, Ehsan Abbasnejad, Kushal Kafle, Robik Shrestha, Christopher Kanan, Anton van den Hengel. [doi]
• Learning Augmented Energy Minimization via Speed ScalingÉtienne Bamas, Andreas Maggiori, Lars Rohwedder, Ola Svensson. [doi]
• Detecting Interactions from Neural Networks via Topological AnalysisZirui Liu, Qingquan Song, Kaixiong Zhou, Ting-Hsiang Wang, Ying Shan, Xia Hu. [doi]
• TaylorGAN: Neighbor-Augmented Policy Update Towards Sample-Efficient Natural Language GenerationChun-Hsing Lin, Siang-Ruei Wu, Hung-yi Lee, Yun-Nung Chen. [doi]
• Learning Restricted Boltzmann Machines with Sparse Latent VariablesGuy Bresler, Rares-Darius Buhai. [doi]
• Active Structure Learning of Causal DAGs via Directed Clique TreesChandler Squires, Sara Magliacane, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam. [doi]
• Task-agnostic Exploration in Reinforcement LearningXuezhou Zhang, Yuzhe Ma, Adish Singla. [doi]
• Locally Differentially Private (Contextual) Bandits LearningKai Zheng 0007, Tianle Cai, Weiran Huang 0001, Zhenguo Li, Liwei Wang 0001. [doi]
• Dual-Resolution Correspondence NetworksXinghui Li, Kai Han, Shuda Li, Victor Prisacariu. [doi]
• Deep Wiener Deconvolution: Wiener Meets Deep Learning for Image DeblurringJiangxin Dong, Stefan Roth 0001, Bernt Schiele. [doi]
• Calibrating CNNs for Lifelong LearningPravendra Singh, Vinay Kumar Verma, Pratik Mazumder, Lawrence Carin, Piyush Rai. [doi]
• MATE: Plugging in Model Awareness to Task Embedding for Meta LearningXiaohan Chen, Zhangyang Wang, Siyu Tang, Krikamol Muandet. [doi]
• RD$^2$: Reward Decomposition with Representation DecompositionZichuan Lin, Derek Yang, Li Zhao, Tao Qin, Guangwen Yang, Tie-Yan Liu. [doi]
• Self-Distillation as Instance-Specific Label SmoothingZhilu Zhang, Mert R. Sabuncu. [doi]
• Evaluating Attribution for Graph Neural NetworksBenjamin Sanchez-Lengeling, Jennifer N. Wei, Brian K. Lee, Emily Reif, Peter Wang, Wesley Wei Qian, Kevin McCloskey, Lucy J. Colwell, Alexander B. Wiltschko. [doi]
• ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse CodingYibo Yang, Hongyang Li, Shan You, Fei Wang 0032, Chen Qian 0006, Zhouchen Lin. [doi]
• Learning Mutational SemanticsBrian Hie, Ellen D. Zhong, Bryan Bryson, Bonnie Berger. [doi]
• Effective Dimension Adaptive Sketching Methods for Faster Regularized Least-Squares OptimizationJonathan Lacotte, Mert Pilanci. [doi]
• Adversarial Crowdsourcing Through Robust Rank-One Matrix CompletionQianqian Ma, Alex Olshevsky. [doi]
• Robust Disentanglement of a Few Factors at a TimeBenjamin Estermann, Markus Marks, Mehmet Fatih Yanik. [doi]
• Sharper Generalization Bounds for Pairwise LearningYunwen Lei, Antoine Ledent, Marius Kloft. [doi]
• Efficient Algorithms for Device Placement of DNN Graph OperatorsJakub Tarnawski, Amar Phanishayee, Nikhil R. Devanur, Divya Mahajan, Fanny Nina Paravecino. [doi]
• Optimal Lottery Tickets via Subset Sum: Logarithmic Over-Parameterization is SufficientAnkit Pensia, Shashank Rajput, Alliot Nagle, Harit Vishwakarma, Dimitris S. Papailiopoulos. [doi]
• Video Object Segmentation with Adaptive Feature Bank and Uncertain-Region RefinementYongQing Liang, Xin Li, Navid Jafari, Jim Chen. [doi]
• Telescoping Density-Ratio EstimationBenjamin Rhodes, Kai Xu, Michael U. Gutmann. [doi]
• Unreasonable Effectiveness of Greedy Algorithms in Multi-Armed Bandit with Many ArmsMohsen Bayati, Nima Hamidi, Ramesh Johari, Khashayar Khosravi. [doi]
• GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private GeneratorsDingfan Chen, Tribhuvanesh Orekondy, Mario Fritz. [doi]
• Stochastic Stein DiscrepanciesJackson Gorham, Anant Raj, Lester Mackey. [doi]
• The Convex Relaxation Barrier, Revisited: Tightened Single-Neuron Relaxations for Neural Network VerificationChristian Tjandraatmadja, Ross Anderson, Joey Huchette, Will Ma, Krunal Patel, Juan Pablo Vielma. [doi]
• Preference-based Reinforcement Learning with Finite-Time GuaranteesYichong Xu, Ruosong Wang, Lin F. Yang, Aarti Singh, Artur Dubrawski. [doi]
• Recovery of sparse linear classifiers from mixture of responsesVenkata Gandikota, Arya Mazumdar, Soumyabrata Pal. [doi]
• Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals MeasurementXin Liu, Josh Fromm, Shwetak N. Patel, Daniel J. McDuff. [doi]
• Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable ModelAlex X. Lee, Anusha Nagabandi, Pieter Abbeel, Sergey Levine. [doi]
• Coherent Hierarchical Multi-Label Classification NetworksEleonora Giunchiglia, Thomas Lukasiewicz. [doi]
• Entrywise convergence of iterative methods for eigenproblemsVasileios Charisopoulos, Austin R. Benson, Anil Damle. [doi]
• Towards Learning Convolutions from ScratchBehnam Neyshabur. [doi]
• Neuron Merging: Compensating for Pruned NeuronsWoojeong Kim, Suhyun Kim, Mincheol Park, Geunseok Jeon. [doi]
• Reinforcement Learning for Control with Multiple FrequenciesJongmin Lee 0004, Byung-Jun Lee 0001, Kee-Eung Kim. [doi]
• Promoting Stochasticity for Expressive Policies via a Simple and Efficient Regularization MethodQi Zhou, Yufei Kuang, Zherui Qiu, Houqiang Li, Jie Wang 0005. [doi]
• On the Optimal Weighted $\ell_2$ Regularization in Overparameterized Linear RegressionDenny Wu, Ji Xu. [doi]
• Unsupervised Learning of Visual Features by Contrasting Cluster AssignmentsMathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, Armand Joulin. [doi]
• Online Matrix Completion with Side InformationMark Herbster, Stephen Pasteris, Lisa Tse. [doi]
• Bad Global Minima Exist and SGD Can Reach ThemShengchao Liu, Dimitris S. Papailiopoulos, Dimitris Achlioptas. [doi]
• Latent Bandits RevisitedJoey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Craig Boutilier. [doi]
• System Identification with Biophysical Constraints: A Circuit Model of the Inner RetinaCornelius Schröder, David Klindt, Sarah Strauß, Katrin Franke, Matthias Bethge, Thomas Euler, Philipp Berens. [doi]
• Steering Distortions to Preserve Classes and Neighbors in Supervised Dimensionality ReductionBenoît Colange, Jaakko Peltonen, Michaël Aupetit, Denys Dutykh, Sylvain Lespinats. [doi]
• Batched Coarse Ranking in Multi-Armed BanditsNikolai Karpov, Qin Zhang 0001. [doi]
• Bayesian Optimization for Iterative LearningVu Nguyen, Sebastian Schulze, Michael A. Osborne. [doi]
• Leveraging Predictions in Smoothed Online Convex Optimization via Gradient-based AlgorithmsYingying Li, Na Li 0002. [doi]
• Gaussian Gated Linear NetworksDavid Budden, Adam H. Marblestone, Eren Sezener, Tor Lattimore, Gregory Wayne, Joel Veness. [doi]
• End-to-End Learning and Intervention in GamesJiayang Li, Jing Yu, Yu Marco Nie, Zhaoran Wang. [doi]
• A Measure-Theoretic Approach to Kernel Conditional Mean EmbeddingsJunhyung Park, Krikamol Muandet. [doi]
• Adversarial Distributional Training for Robust Deep LearningYinpeng Dong, Zhijie Deng, Tianyu Pang, Jun Zhu 0001, Hang Su 0006. [doi]
• Refactoring Policy for Compositional Generalizability using Self-Supervised Object ProposalsTongzhou Mu, Jiayuan Gu, Zhiwei Jia, Hao Tang, Hao Su 0001. [doi]
• Error Bounds of Imitating Policies and EnvironmentsTian Xu, Ziniu Li, Yang Yu. [doi]
• Efficient Exact Verification of Binarized Neural NetworksKai Jia, Martin Rinard. [doi]
• Reconciling Modern Deep Learning with Traditional Optimization Analyses: The Intrinsic Learning RateZhiyuan Li 0005, Kaifeng Lyu, Sanjeev Arora. [doi]
• Dual Instrumental Variable RegressionKrikamol Muandet, Arash Mehrjou, Si Kai Lee, Anant Raj. [doi]
• Predictive coding in balanced neural networks with noise, chaos and delaysJonathan Kadmon, Jonathan Timcheck, Surya Ganguli. [doi]
• Fixed-Support Wasserstein Barycenters: Computational Hardness and Fast AlgorithmTianyi Lin, Nhat Ho, Xi Chen, Marco Cuturi, Michael I. Jordan. [doi]
• Promoting Coordination through Policy Regularization in Multi-Agent Deep Reinforcement LearningJulien Roy, Paul Barde, Félix G. Harvey, Derek Nowrouzezahrai, Chris Pal. [doi]
• SDF-SRN: Learning Signed Distance 3D Object Reconstruction from Static ImagesChen-Hsuan Lin, Chaoyang Wang, Simon Lucey. [doi]
• Acceleration with a Ball Optimization OracleYair Carmon, Arun Jambulapati, Qijia Jiang, Yujia Jin, Yin Tat Lee, Aaron Sidford, Kevin Tian. [doi]
• Learning Kernel Tests Without Data SplittingJonas M. Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet. [doi]
• Fairness in Streaming Submodular Maximization: Algorithms and HardnessMarwa El Halabi, Slobodan Mitrovic, Ashkan Norouzi-Fard, Jakab Tardos, Jakub Tarnawski. [doi]
• Learning Implicit Functions for Topology-Varying Dense 3D Shape CorrespondenceFeng Liu, Xiaoming Liu. [doi]
• Functional Regularization for Representation Learning: A Unified Theoretical PerspectiveSiddhant Garg, Yingyu Liang. [doi]
• Distribution-free binary classification: prediction sets, confidence intervals and calibrationChirag Gupta, Aleksandr Podkopaev, Aaditya Ramdas. [doi]
• Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test ExamplesShafi Goldwasser, Adam Tauman Kalai, Yael Kalai, Omar Montasser. [doi]
• Kernel Alignment Risk Estimator: Risk Prediction from Training DataArthur Jacot, Berfin Simsek, Francesco Spadaro, Clément Hongler, Franck Gabriel. [doi]
• Exact Recovery of Mangled Clusters with Same-Cluster QueriesMarco Bressan 0002, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice. [doi]
• Synbols: Probing Learning Algorithms with Synthetic DatasetsAlexandre Lacoste, Pau Rodríguez López, Frederic Branchaud-Charron, Parmida Atighehchian, Massimo Caccia, Issam Hadj Laradji, Alexandre Drouin, Matt Craddock, Laurent Charlin, David Vázquez. [doi]
• Simplify and Robustify Negative Sampling for Implicit Collaborative FilteringJingtao Ding, Yuhan Quan, Quanming Yao, Yong Li 0008, Depeng Jin. [doi]
• Hardness of Learning Neural Networks with Natural WeightsAmit Daniely, Gal Vardi. [doi]
• Depth Uncertainty in Neural NetworksJavier Antorán, James Urquhart Allingham, José Miguel Hernández-Lobato. [doi]
• Geometric Exploration for Online ControlOrestis Plevrakis, Elad Hazan. [doi]
• Instance-based Generalization in Reinforcement LearningMartín Bertrán, Natalia Martínez, Mariano Phielipp, Guillermo Sapiro. [doi]
• NanoFlow: Scalable Normalizing Flows with Sublinear Parameter ComplexitySang Gil Lee, Sungwon Kim, Sungroh Yoon. [doi]
• Breaking the Communication-Privacy-Accuracy TrilemmaWei-Ning Chen, Peter Kairouz, Ayfer Özgür. [doi]
• Off-policy Policy Evaluation For Sequential Decisions Under Unobserved ConfoundingHongseok Namkoong, Ramtin Keramati, Steve Yadlowsky, Emma Brunskill. [doi]
• Limits on Testing Structural Changes in Ising ModelsAditya Gangrade, Bobak Nazer, Venkatesh Saligrama. [doi]
• Program Synthesis with Pragmatic CommunicationYewen Pu, Kevin Ellis, Marta Kryven, Josh Tenenbaum 0001, Armando Solar-Lezama. [doi]
• Large-Scale Methods for Distributionally Robust OptimizationDaniel Levy, Yair Carmon, John C. Duchi, Aaron Sidford. [doi]
• Fairness with Overlapping Groups; a Probabilistic PerspectiveForest Yang, Mouhamadou Cisse, Oluwasanmi Koyejo. [doi]
• Steady State Analysis of Episodic Reinforcement LearningBojun Huang. [doi]
• Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack TransferabilityNathan Inkawhich, Kevin J. Liang, Binghui Wang, Matthew Inkawhich, Lawrence Carin, Yiran Chen. [doi]
• Minimax Lower Bounds for Transfer Learning with Linear and One-hidden Layer Neural NetworksSeyed Mohammadreza Mousavi Kalan, Zalan Fabian, Salman Avestimehr, Mahdi Soltanolkotabi. [doi]
• Learning Parities with Neural NetworksAmit Daniely, Eran Malach. [doi]
• Sample-Efficient Reinforcement Learning of Undercomplete POMDPsChi Jin, Sham M. Kakade, Akshay Krishnamurthy, Qinghua Liu. [doi]
• SLIP: Learning to predict in unknown dynamical systems with long-term memoryParia Rashidinejad, Jiantao Jiao, Stuart Russell. [doi]
• Learning to Play No-Press Diplomacy with Best Response Policy IterationThomas W. Anthony, Tom Eccles, Andrea Tacchetti, János Kramár, Ian M. Gemp, Thomas C. Hudson, Nicolas Porcel, Marc Lanctot, Julien Pérolat, Richard Everett 0001, Satinder Singh, Thore Graepel, Yoram Bachrach. [doi]
• Your Classifier can Secretly Suffice Multi-Source Domain AdaptationNaveen Venkat, Jogendra Nath Kundu, Durgesh Kumar Singh, Ambareesh Revanur, Venkatesh Babu R.. [doi]
• Non-Euclidean Universal ApproximationAnastasis Kratsios, Ievgen Bilokopytov. [doi]
• GRAF: Generative Radiance Fields for 3D-Aware Image SynthesisKatja Schwarz, Yiyi Liao, Michael Niemeyer, Andreas Geiger 0001. [doi]
• Geometric All-way Boolean Tensor DecompositionChanglin Wan, Wennan Chang, Tong Zhao, Sha Cao, Chi Zhang. [doi]
• Differentially Private Clustering: Tight Approximation RatiosBadih Ghazi, Ravi Kumar 0001, Pasin Manurangsi. [doi]
• On Infinite-Width HypernetworksEtai Littwin, Tomer Galanti, Lior Wolf, Greg Yang. [doi]
• Nimble: Lightweight and Parallel GPU Task Scheduling for Deep LearningWoosuk Kwon, Gyeong-In Yu, Eunji Jeong, Byung-Gon Chun. [doi]
• Profile Entropy: A Fundamental Measure for the Learnability and Compressibility of DistributionsYi Hao, Alon Orlitsky. [doi]
• Elastic-InfoGAN: Unsupervised Disentangled Representation Learning in Class-Imbalanced DataUtkarsh Ojha, Krishna Kumar Singh, Cho-Jui Hsieh, Yong Jae Lee. [doi]
• Learning to Decode: Reinforcement Learning for Decoding of Sparse Graph-Based Channel CodesSalman Habib, Allison Beemer, Jörg Kliewer. [doi]
• Graph Random Neural Networks for Semi-Supervised Learning on GraphsWenzheng Feng, Jie Zhang, Yuxiao Dong, Yu Han, Huanbo Luan, Qian Xu, Qiang Yang, Evgeny Kharlamov, Jie Tang 0001. [doi]
• Ode to an ODEKrzysztof Marcin Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques E. Slotine, Jacob Varley, Honglak Lee, Adrian Weller, Vikas Sindhwani. [doi]
• Non-reversible Gaussian processes for identifying latent dynamical structure in neural dataVirginia Rutten, Alberto Bernacchia, Maneesh Sahani, Guillaume Hennequin. [doi]
• Understanding and Exploring the Network with Stochastic ArchitecturesZhijie Deng, Yinpeng Dong, Shifeng Zhang, Jun Zhu 0001. [doi]
• Self-Adaptive Training: beyond Empirical Risk MinimizationLang Huang, Chao Zhang 0001, Hongyang Zhang 0001. [doi]
• On Correctness of Automatic Differentiation for Non-Differentiable FunctionsWonyeol Lee 0001, Hangyeol Yu, Xavier Rival, Hongseok Yang. [doi]
• Dual-Free Stochastic Decentralized Optimization with Variance ReductionHadrien Hendrikx, Francis R. Bach, Laurent Massoulié. [doi]
• Modular Meta-Learning with ShrinkageYutian Chen, Abram L. Friesen, Feryal Behbahani, Arnaud Doucet, David Budden, Matthew Hoffman 0002, Nando de Freitas. [doi]
• Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoderZhisheng Xiao, Qing Yan, Yali Amit. [doi]