| 2022 | State Dependent Performative Prediction with Stochastic Approximation. | Qiang Li, Hoi-To Wai |
| 2022 | Momentum Accelerates the Convergence of Stochastic AUPRC Maximization. | Guanghui Wang, Ming Yang, Lijun Zhang, Tianbao Yang |
| 2022 | An Alternate Policy Gradient Estimator for Softmax Policies. | Shivam Garg, Samuele Tosatto, Yangchen Pan, Martha White, Rupam Mahmood |
| 2022 | Non-stationary Online Learning with Memory and Non-stochastic Control. | Peng Zhao, Yu-Xiang Wang, Zhi-Hua Zhou |
| 2022 | Adaptive Private-K-Selection with Adaptive K and Application to Multi-label PATE. | Yuqing Zhu, Yu-Xiang Wang |
| 2022 | Optimal Accounting of Differential Privacy via Characteristic Function. | Yuqing Zhu, Jinshuo Dong, Yu-Xiang Wang |
| 2022 | Adversarial Tracking Control via Strongly Adaptive Online Learning with Memory. | Zhiyu Zhang, Ashok Cutkosky, Ioannis Ch. Paschalidis |
| 2022 | Pairwise Supervision Can Provably Elicit a Decision Boundary. | Han Bao, Takuya Shimada, Liyuan Xu, Issei Sato, Masashi Sugiyama |
| 2022 | Co-Regularized Adversarial Learning for Multi-Domain Text Classification. | Yuan Wu, Diana Inkpen, Ahmed El-Roby |
| 2022 | Robust Stochastic Linear Contextual Bandits Under Adversarial Attacks. | Qin Ding, Cho-Jui Hsieh, James Sharpnack |
| 2022 | Fast Sparse Classification for Generalized Linear and Additive Models. | Jiachang Liu, Chudi Zhong, Margo I. Seltzer, Cynthia Rudin |
| 2022 | Increasing the accuracy and resolution of precipitation forecasts using deep generative models. | Ilan Price, Stephan Rasp |
| 2022 | Private Sequential Hypothesis Testing for Statisticians: Privacy, Error Rates, and Sample Size. | Wanrong Zhang, Yajun Mei, Rachel Cummings |
| 2022 | Differentially Private Densest Subgraph. | Alireza Farhadi, MohammadTaghi Hajiaghayi, Elaine Shi |
| 2022 | Efficient interventional distribution learning in the PAC framework. | Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, Vedant Raval, N. Variyam Vinodchandran |
| 2022 | Provable Adversarial Robustness for Fractional Lp Threat Models. | Alexander Levine, Soheil Feizi |
| 2022 | Learning Sparse Fixed-Structure Gaussian Bayesian Networks. | Arnab Bhattacharyya, Davin Choo, Rishikesh Gajjala, Sutanu Gayen, Yuhao Wang |
| 2022 | On Uncertainty Estimation by Tree-based Surrogate Models in Sequential Model-based Optimization. | Jungtaek Kim, Seungjin Choi |
| 2021 | Deep Fourier Kernel for Self-Attentive Point Processes. | Shixiang Zhu, Minghe Zhang, Ruyi Ding, Yao Xie |
| 2021 | Taming heavy-tailed features by shrinkage. | Ziwei Zhu, Wenjing Zhou |
| 2021 | One-pass Stochastic Gradient Descent in overparametrized two-layer neural networks. | Hanjing Zhu, Jiaming Xu |
| 2021 | Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation. | Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schlkopf |
| 2021 | No-Regret Reinforcement Learning with Heavy-Tailed Rewards. | Vincent Zhuang, Yanan Sui |
| 2021 | Curriculum Learning by Optimizing Learning Dynamics. | Tianyi Zhou, Shengjie Wang, Jeff A. Bilmes |
| 2021 | Towards Understanding the Behaviors of Optimal Deep Active Learning Algorithms. | Yilun Zhou, Adithya Renduchintala, Xian Li, Sida Wang, Yashar Mehdad, Asish Ghoshal |