| 2026 | COLT | Taming the Monster Every Context: Complexity Measure and Unified Framework for Offline-Oracle Efficient Contextual Bandits. | Hao Qin, Chicheng Zhang |
| 2026 | WiOpt | Physics-Informed Parametric Bandits for Beam Alignment in mmWave Communications. | Hao Qin, Thang Duong, Ming F. Li, Chicheng Zhang |
| 2025 | COLT | Towards Fundamental Limits for Active Multi-distribution Learning. | Chicheng Zhang, Yihan Zhou |
| 2024 | AISTATS | Efficient Active Learning Halfspaces with Tsybakov Noise: A Non-convex Optimization Approach. | Yinan Li, Chicheng Zhang |
| 2024 | ICLR | The Human-AI Substitution game: active learning from a strategic labeler. | Tom Yan, Chicheng Zhang |
| 2024 | ICML | Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank Bandits. | Kyoungseok Jang, Chicheng Zhang, Kwang-Sung Jun |
| 2024 | ICML | Agnostic Interactive Imitation Learning: New Theory and Practical Algorithms. | Yichen Li, Chicheng Zhang |
| 2023 | WiOpt | Fair Coexistence of Heterogeneous Networks: A Novel Probabilistic Multi-Armed Bandit Approach. | Zhiwu Guo, Chicheng Zhang, Ming Li, Marwan Krunz |
| 2022 | AISTATS | Margin-distancing for safe model explanation. | Tom Yan, Chicheng Zhang |
| 2022 | ICML | Thompson Sampling for Robust Transfer in Multi-Task Bandits. | Zhi Wang, Chicheng Zhang, Kamalika Chaudhuri |
| 2022 | ICML | Active fairness auditing. | Tom Yan, Chicheng Zhang |
| 2021 | AISTATS | Active Online Learning with Hidden Shifting Domains. | Yining Chen, Haipeng Luo, Tengyu Ma, Chicheng Zhang |
| 2021 | AISTATS | Multitask Bandit Learning Through Heterogeneous Feedback Aggregation. | Zhi Wang, Chicheng Zhang, Manish Kumar Singh, Laurel D. Riek, Kamalika Chaudhuri |
| 2021 | ALT | Attribute-Efficient Learning of Halfspaces with Malicious Noise: Near-Optimal Label Complexity and Noise Tolerance. | Jie Shen, Chicheng Zhang |
| 2021 | COLT | Improved Algorithms for Efficient Active Learning Halfspaces with Massart and Tsybakov Noise. | Chicheng Zhang, Yinan Li |
| 2020 | ICLR | Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds. | Jordan T. Ash, Chicheng Zhang, Akshay Krishnamurthy, John Langford, Alekh Agarwal |
| 2019 | COLT | Contextual bandits with continuous actions: Smoothing, zooming, and adapting. | Akshay Krishnamurthy, John Langford, Aleksandrs Slivkins, Chicheng Zhang |
| 2019 | ICML | Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case. | Alina Beygelzimer, Dvid Pl, Balzs Szrnyi, Devanathan Thiruvenkatachari, Chen-Yu Wei, Chicheng Zhang |
| 2019 | ICML | Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback. | Chicheng Zhang, Alekh Agarwal, Hal Daum III, John Langford, Sahand Negahban |
| 2018 | COLT | Efficient active learning of sparse halfspaces. | Chicheng Zhang |
| 2017 | ICML | Efficient Online Bandit Multiclass Learning with Õ(√T) Regret. | Alina Beygelzimer, Francesco Orabona, Chicheng Zhang |
| 2016 | COLT | The Extended Littlestone's Dimension for Learning with Mistakes and Abstentions. | Chicheng Zhang, Kamalika Chaudhuri |