| 2020 | Learning Entangled Single-Sample Distributions via Iterative Trimming. | Hui Yuan, Yingyu Liang |
| 2020 | A Theoretical Case Study of Structured Variational Inference for Community Detection. | Mingzhang Yin, Y. X. Rachel Wang, Purnamrita Sarkar |
| 2020 | Asymptotically Efficient Off-Policy Evaluation for Tabular Reinforcement Learning. | Ming Yin, Yu-Xiang Wang |
| 2020 | Fast and Accurate Ranking Regression. | Ilkay Yildiz, Jennifer G. Dy, Deniz Erdogmus, Jayashree Kalpathy-Cramer, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, Stratis Ioannidis |
| 2020 | Optimization of Graph Total Variation via Active-Set-based Combinatorial Reconditioning. | Zhenzhang Ye, Thomas Mllenhoff, Tao Wu, Daniel Cremers |
| 2020 | "Bring Your Own Greedy"+Max: Near-Optimal 1/2-Approximations for Submodular Knapsack. | Grigory Yaroslavtsev, Samson Zhou, Dmitrii Avdiukhin |
| 2020 | A Linear-time Independence Criterion Based on a Finite Basis Approximation. | Longfei Yan, W. Bastiaan Kleijn, Thushara D. Abhayapala |
| 2020 | Laplacian-Regularized Graph Bandits: Algorithms and Theoretical Analysis. | Kaige Yang, Laura Toni, Xiaowen Dong |
| 2020 | Robustness for Non-Parametric Classification: A Generic Attack and Defense. | Yao-Yuan Yang, Cyrus Rashtchian, Yizhen Wang, Kamalika Chaudhuri |
| 2020 | Adaptive Online Kernel Sampling for Vertex Classification. | Peng Yang, Ping Li |
| 2020 | Amortized Inference of Variational Bounds for Learning Noisy-OR. | Yiming Yan, Melissa Ailem, Fei Sha |
| 2020 | A Stein Goodness-of-fit Test for Directional Distributions. | Wenkai Xu, Takeru Matsuda |
| 2020 | Auditing ML Models for Individual Bias and Unfairness. | Songkai Xue, Mikhail Yurochkin, Yuekai Sun |
| 2020 | Thresholding Bandit Problem with Both Duels and Pulls. | Yichong Xu, Xi Chen, Aarti Singh, Artur Dubrawski |
| 2020 | Linear Convergence of Adaptive Stochastic Gradient Descent. | Yuege Xie, Xiaoxia Wu, Rachel A. Ward |
| 2020 | Stochastic Linear Contextual Bandits with Diverse Contexts. | Weiqiang Wu, Jing Yang, Cong Shen |
| 2020 | Graph DNA: Deep Neighborhood Aware Graph Encoding for Collaborative Filtering. | Liwei Wu, Hsiang-Fu Yu, Nikhil Rao, James Sharpnack, Cho-Jui Hsieh |
| 2020 | Causal Mosaic: Cause-Effect Inference via Nonlinear ICA and Ensemble Method. | Pengzhou Wu, Kenji Fukumizu |
| 2020 | On Minimax Optimality of GANs for Robust Mean Estimation. | Kaiwen Wu, Gavin Weiguang Ding, Ruitong Huang, Yaoliang Yu |
| 2020 | Minimax Testing of Identity to a Reference Ergodic Markov Chain. | Geoffrey Wolfer, Aryeh Kontorovich |
| 2020 | Approximate Cross-validation: Guarantees for Model Assessment and Selection. | Ashia C. Wilson, Maximilian Kasy, Lester Mackey |
| 2020 | An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise. | Yeming Wen, Kevin Luk, Maxime Gazeau, Guodong Zhang, Harris Chan, Jimmy Ba |
| 2020 | Non-Parametric Calibration for Classification. | Jonathan Wenger, Hedvig Kjellstrm, Rudolph Triebel |
| 2020 | Optimized Score Transformation for Fair Classification. | Dennis Wei, Karthikeyan Natesan Ramamurthy, Flvio P. Calmon |
| 2020 | Structured Conditional Continuous Normalizing Flows for Efficient Amortized Inference in Graphical Models. | Christian Weilbach, Boyan Beronov, Frank Wood, William Harvey |