| 2021 | The Base Measure Problem and its Solution. | Alexey Radul, Boris Alexeev |
| 2021 | Adaptive Sampling for Fast Constrained Maximization of Submodular Functions. | Francesco Quinzan, Vanja Doskoc, Andreas Gbel, Tobias Friedrich |
| 2021 | On the Memory Mechanism of Tensor-Power Recurrent Models. | Hejia Qiu, Chao Li, Ying Weng, Zhun Sun, Xingyu He, Qibin Zhao |
| 2021 | Understanding Gradient Clipping In Incremental Gradient Methods. | Jiang Qian, Yuren Wu, Bojin Zhuang, Shaojun Wang, Jing Xiao |
| 2021 | An Analysis of the Adaptation Speed of Causal Models. | Rmi Le Priol, Reza Babanezhad, Yoshua Bengio, Simon Lacoste-Julien |
| 2021 | Statistical Guarantees for Transformation Based Models with applications to Implicit Variational Inference. | Sean Plummer, Shuang Zhou, Anirban Bhattacharya, David B. Dunson, Debdeep Pati |
| 2021 | Designing Transportable Experiments Under S-admissability. | My Phan, David Arbour, Drew Dimmery, Anup B. Rao |
| 2021 | Differentially Private Online Submodular Maximization. | Sebastian Perez-Salazar, Rachel Cummings |
| 2021 | Regression Discontinuity Design under Self-selection. | Sida Peng, Yang Ning |
| 2021 | Uniform Consistency of Cross-Validation Estimators for High-Dimensional Ridge Regression. | Pratik Patil, Yuting Wei, Alessandro Rinaldo, Ryan J. Tibshirani |
| 2021 | A unified view of likelihood ratio and reparameterization gradients. | Paavo Parmas, Masashi Sugiyama |
| 2021 | Local Competition and Stochasticity for Adversarial Robustness in Deep Learning. | Konstantinos P. Panousis, Sotirios Chatzis, Antonios Alexos, Sergios Theodoridis |
| 2021 | Fourier Bases for Solving Permutation Puzzles. | Horace Pan, Risi Kondor |
| 2021 | Sketch based Memory for Neural Networks. | Rina Panigrahy, Xin Wang, Manzil Zaheer |
| 2021 | Stochastic Bandits with Linear Constraints. | Aldo Pacchiano, Mohammad Ghavamzadeh, Peter L. Bartlett, Heinrich Jiang |
| 2021 | Training a Single Bandit Arm. | Eren Ozbay, Vijay Kamble |
| 2021 | A Theoretical Characterization of Semi-supervised Learning with Self-training for Gaussian Mixture Models. | Samet Oymak, Talha Cihad Gulcu |
| 2021 | Associative Convolutional Layers. | Hamed Omidvar, Vahideh Akhlaghi, Hao Su, Massimo Franceschetti, Rajesh K. Gupta |
| 2021 | Unconstrained MAP Inference, Exponentiated Determinantal Point Processes, and Exponential Inapproximability. | Naoto Ohsaka |
| 2021 | Novel Change of Measure Inequalities with Applications to PAC-Bayesian Bounds and Monte Carlo Estimation. | Yuki Ohnishi, Jean Honorio |
| 2021 | Spectral Tensor Train Parameterization of Deep Learning Layers. | Anton Obukhov, Maxim V. Rakhuba, Alexander Liniger, Zhiwu Huang, Stamatios Georgoulis, Dengxin Dai, Luc Van Gool |
| 2021 | Group testing for connected communities. | Pavlos Nikolopoulos, Sundara Rajan Srinivasavaradhan, Tao Guo, Christina Fragouli, Suhas N. Diggavi |
| 2021 | Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes. | Nhuong V. Nguyen, Toan N. Nguyen, Phuong Ha Nguyen, Quoc Tran-Dinh, Lam M. Nguyen, Marten van Dijk |
| 2021 | Predictive Complexity Priors. | Eric T. Nalisnick, Jonathan Gordon, Jos Miguel Hernndez-Lobato |
| 2021 | Budgeted and Non-Budgeted Causal Bandits. | Vineet Nair, Vishakha Patil, Gaurav Sinha |