Beyond Disagreement-Based Agnostic Active Learning. - Chicheng Zhang; Kamalika Chaudhuri (NIPS, 2014)

Active Learning from Weak and Strong Labelers. - Chicheng Zhang; Kamalika Chaudhuri (NIPS, 2015)

Spectral Learning of Large Structured HMMs for Comparative Epigenomics. - Chicheng Zhang; Jimin Song; Kamalika Chaudhuri; Kevin C. Chen (NIPS, 2015)

The Extended Littlestone's Dimension for Learning with Mistakes and Abstentions. - Chicheng Zhang; Kamalika Chaudhuri (COLT, 2016)

Search Improves Label for Active Learning. - Alina Beygelzimer; Daniel J. Hsu; John Langford 001; Chicheng Zhang (NIPS, 2016)

Efficient Online Bandit Multiclass Learning with Õ(√T) Regret. - Alina Beygelzimer; Francesco Orabona; Chicheng Zhang (ICML, 2017)

Revisiting Perceptron: Efficient and Label-Optimal Learning of Halfspaces. - Songbai Yan; Chicheng Zhang (NIPS, 2017)

Efficient Online Bandit Multiclass Learning with $ tilde{O}( sqrt{T})$ Regret. - Alina Beygelzimer; Francesco Orabona; Chicheng Zhang (CoRR, 2017)

Revisiting Perceptron: Efficient and Label-Optimal Active Learning of Halfspaces. - Songbai Yan; Chicheng Zhang (CoRR, 2017)

Active Learning and Confidence-rated Prediction. - Chicheng Zhang (2017)

Efficient active learning of sparse halfspaces. - Chicheng Zhang (COLT, 2018)

Spectral Learning of Binomial HMMs for DNA Methylation Data. - Chicheng Zhang; Eran A. Mukamel; Kamalika Chaudhuri (CoRR, 2018)

Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case. - Alina Beygelzimer; Dávid Pál; Balázs Szörényi; Devanathan Thiruvenkatachari; Chen-Yu Wei; Chicheng Zhang (ICML, 2019)

Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback. - Chicheng Zhang; Alekh Agarwal; Hal Daumé III; John Langford 001; Sahand Negahban (ICML, 2019)

Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds. - Jordan T. Ash; Chicheng Zhang; Akshay Krishnamurthy; John Langford 001; Alekh Agarwal (ICLR, 2020)

Crush Optimism with Pessimism: Structured Bandits Beyond Asymptotic Optimality. - Kwang-Sung Jun; Chicheng Zhang (NeurIPS, 2020)

Efficient Contextual Bandits with Continuous Actions. - Maryam Majzoubi; Chicheng Zhang; Rajan Chari; Akshay Krishnamurthy; John Langford 001; Aleksandrs Slivkins (NeurIPS, 2020)

Efficient active learning of sparse halfspaces with arbitrary bounded noise. - Chicheng Zhang; Jie Shen 005; Pranjal Awasthi (NeurIPS, 2020)

Active Online Domain Adaptation. - Yining Chen; Haipeng Luo; Tengyu Ma 001; Chicheng Zhang (CoRR, 2020)

Contextual Bandits with Continuous Actions: Smoothing, Zooming, and Adapting. - Akshay Krishnamurthy; John Langford 001; Aleksandrs Slivkins; Chicheng Zhang (J. Mach. Learn. Res., 2020)

Active Online Learning with Hidden Shifting Domains. - Yining Chen; Haipeng Luo; Tengyu Ma 001; Chicheng Zhang (AISTATS, 2021)

Multitask Bandit Learning Through Heterogeneous Feedback Aggregation. - Zhi Wang 013; Chicheng Zhang; Manish Kumar Singh 002; Laurel D. Riek; Kamalika Chaudhuri (AISTATS, 2021)

Attribute-Efficient Learning of Halfspaces with Malicious Noise: Near-Optimal Label Complexity and Noise Tolerance. - Jie Shen 005; Chicheng Zhang (ALT, 2021)

Improved Algorithms for Efficient Active Learning Halfspaces with Massart and Tsybakov Noise. - Chicheng Zhang; Yinan Li (COLT, 2021)

Provably efficient multi-task reinforcement learning with model transfer. - Chicheng Zhang; Zhi Wang 013 (NeurIPS, 2021)

Improving the trustworthiness of image classification models by utilizing bounding-box annotations. - Dharma KC; Chicheng Zhang (CoRR, 2021)

SIM-ECG: A Signal Importance Mask-driven ECGClassification System. - Dharma KC; Chicheng Zhang; Chris Gniady; Parth Sandeep Agarwal; Sushil Sharma (CoRR, 2021)

Margin-distancing for safe model explanation. - Tom Yan; Chicheng Zhang (AISTATS, 2022)

Thompson Sampling for Robust Transfer in Multi-Task Bandits. - Zhi Wang 013; Chicheng Zhang; Kamalika Chaudhuri (ICML, 2022)

Active fairness auditing. - Tom Yan; Chicheng Zhang (ICML, 2022)

PopArt: Efficient Sparse Regression and Experimental Design for Optimal Sparse Linear Bandits. - Kyoungseok Jang; Chicheng Zhang; Kwang-Sung Jun (NeurIPS, 2022)

On Efficient Online Imitation Learning via Classification. - Yichen Li; Chicheng Zhang (NeurIPS, 2022)

Hierarchical Unimodal Bandits. - Tianchi Zhao; Chicheng Zhang; Ming Li (ECML/PKDD (4), 2022)

Kullback-Leibler Maillard Sampling for Multi-armed Bandits with Bounded Rewards. - Hao Qin; Kwang-Sung Jun; Chicheng Zhang (NeurIPS, 2023)

Fair Coexistence of Heterogeneous Networks: A Novel Probabilistic Multi-Armed Bandit Approach. - Zhiwu Guo; Chicheng Zhang; Ming Li 003; Marwan Krunz (WiOpt, 2023)

Ensemble-based Interactive Imitation Learning. - Yichen Li; Chicheng Zhang (CoRR, 2023)

Efficient Active Learning Halfspaces with Tsybakov Noise: A Non-convex Optimization Approach. - Yinan Li; Chicheng Zhang (AISTATS, 2024)

The Human-AI Substitution game: active learning from a strategic labeler. - Tom Yan; Chicheng Zhang (ICLR, 2024)

Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank Bandits. - Kyoungseok Jang; Chicheng Zhang; Kwang-Sung Jun (ICML, 2024)

Agnostic Interactive Imitation Learning: New Theory and Practical Algorithms. - Yichen Li; Chicheng Zhang (ICML, 2024)

Beyond task diversity: provable representation transfer for sequential multitask linear bandits. - Thang Duong; Zhi Wang 013; Chicheng Zhang (NeurIPS, 2024)

A Note on Sample Complexity of Interactive Imitation Learning with Log Loss. - Yichen Li; Chicheng Zhang (CoRR, 2024)

Towards Fundamental Limits for Active Multi-distribution Learning. - Chicheng Zhang; Yihan Zhou (COLT, 2025)

Efficient Fair Probabilistic Multi-armed Bandit for Real-Time Resource Allocation in Spectrum Sharing. - Zhiwu Guo; Chicheng Zhang; Ming Li 003; Marwan Krunz (DySPAN, 2025)

Beyond Task Diversity: Provable Representation Transfer for Sequential Multi-Task Linear Bandits. - Thang Duong; Zhi Wang; Chicheng Zhang (CoRR, 2025)

Achieving adaptivity and optimality for multi-armed bandits using Exponential-Kullback Leiblier Maillard Sampling. - Hao Qin; Kwang-Sung Jun; Chicheng Zhang (CoRR, 2025)

Improving the Data-efficiency of Reinforcement Learning by Warm-starting with LLM. - Thang Duong; Minglai Yang 002; Chicheng Zhang (CoRR, 2025)