| 2024 | Low-rank Matrix Bandits with Heavy-tailed Rewards. | Yue Kang, Cho-Jui Hsieh, Thomas Chun Man Lee |
| 2024 | Convergence Behavior of an Adversarial Weak Supervision Method. | Steven An, Sanjoy Dasgupta |
| 2024 | Knowledge Intensive Learning of Credal Networks. | Saurabh Mathur, Alessandro Antonucci, Sriraam Natarajan |
| 2024 | Support Recovery in Sparse PCA with General Missing Data. | Hanbyul Lee, Qifan Song, Jean Honorio |
| 2024 | Optimizing Language Models for Human Preferences is a Causal Inference Problem. | Victoria Lin, Eli Ben-Michael, Louis-Philippe Morency |
| 2023 | Regularized online DR-submodular optimization. | Pengyu Zuo, Yao Wang, Shaojie Tang |
| 2023 | MixupE: Understanding and improving Mixup from directional derivative perspective. | Yingtian Zou, Vikas Verma, Sarthak Mittal, Wai Hoh Tang, Hieu Pham, Juho Kannala, Yoshua Bengio, Arno Solin, Kenji Kawaguchi |
| 2023 | AUC Maximization in Imbalanced Lifelong Learning. | Xiangyu Zhu, Jie Hao, Yunhui Guo, Mingrui Liu |
| 2023 | Convergence rates for localized actor-critic in networked Markov potential games. | Zhaoyi Zhou, Zaiwei Chen, Yiheng Lin, Adam Wierman |
| 2023 | Learning robust representation for reinforcement learning with distractions by reward sequence prediction. | Qi Zhou, Jie Wang, Qiyuan Liu, Yufei Kuang, Wengang Zhou, Houqiang Li |
| 2023 | RDM-DC: Poisoning Resilient Dataset Condensation with Robust Distribution Matching. | Tianhang Zheng, Baochun Li |
| 2023 | Conditional counterfactual causal effect for individual attribution. | Ruiqi Zhao, Lei Zhang, Shengyu Zhu, Zitong Lu, Zhenhua Dong, Chaoliang Zhang, Jun Xu, Zhi Geng, Yangbo He |
| 2023 | Conditionally optimistic exploration for cooperative deep multi-agent reinforcement learning. | Xutong Zhao, Yangchen Pan, Chenjun Xiao, Sarath Chandar, Janarthanan Rajendran |
| 2023 | Fast Teammate Adaptation in the Presence of Sudden Policy Change. | Ziqian Zhang, Lei Yuan, Lihe Li, Ke Xue, Chengxing Jia, Cong Guan, Chao Qian, Yang Yu |
| 2023 | Energy-based Predictive Representations for Partially Observed Reinforcement Learning. | Tianjun Zhang, Tongzheng Ren, Chenjun Xiao, Wenli Xiao, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai |
| 2023 | Greed is good: correspondence recovery for unlabeled linear regression. | Hang Zhang, Ping Li |
| 2023 | Provably efficient representation selection in Low-rank Markov Decision Processes: from online to offline RL. | Weitong Zhang, Jiafan He, Dongruo Zhou, Amy Zhang, Quanquan Gu |
| 2023 | Graph Self-supervised Learning via Proximity Distribution Minimization. | Tianyi Zhang, Zhenwei Dai, Zhaozhuo Xu, Anshumali Shrivastava |
| 2023 | Online estimation of similarity matrices with incomplete data. | Fangchen Yu, Yicheng Zeng, Jianfeng Mao, Wenye Li |
| 2023 | Towards Physically Reliable Molecular Representation Learning. | Seunghoon Yi, Youngwoo Cho, Jinhwan Sul, Seung Woo Ko, Soo Kyung Kim, Jaegul Choo, Hongkee Yoon, Joonseok Lee |
| 2023 | Mitigating Transformer Overconfidence via Lipschitz Regularization. | Wenqian Ye, Yunsheng Ma, Xu Cao, Kun Tang |
| 2023 | Pessimistic Model Selection for Offline Deep Reinforcement Learning. | Chao-Han Huck Yang, Zhengling Qi, Yifan Cui, Pin-Yu Chen |
| 2023 | Multi-modal differentiable unsupervised feature selection. | Junchen Yang, Ofir Lindenbaum, Yuval Kluger, Ariel Jaffe |
| 2023 | MMEL: A Joint Learning Framework for Multi-Mention Entity Linking. | Chengmei Yang, Bowei He, Yimeng Wu, Chao Xing, Lianghua He, Chen Ma |
| 2023 | Mixture of Normalizing Flows for European Option Pricing. | Yongxin Yang, Timothy M. Hospedales |