← Authors

Chicheng Zhang

33 papers · 2014–2025 · 7 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (6) 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (39) πŸƒ Academic Marathon (11) 🧭 Keyword Pioneer 🐝 Cross-Pollinator (15) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (7) πŸ† Keyword Champion (8) πŸ‘‘ Triple Crown πŸ”¬ Deep Specialist (12) πŸ—ƒοΈ Keyword Collector (110) ⚑ Prolific Year (5) πŸ’Ž Century Club (33) πŸ”₯ Unstoppable (12) πŸ“ˆ Trend Setter

Conferences

NIPS (13) ICML (7) COLT (5) AISTATS (4) ICLR (2) ALT (1) JMLR (1)

Top co-authors

Kamalika Chaudhuri (6) John Langford (6) Kwang-Sung Jun (4) Akshay Krishnamurthy (4) Zhi Wang (4) Alina Beygelzimer (3) Aleksandrs Slivkins (3) Tom Yan (3) Alekh Agarwal (2) Yichen Li (2)

Research topics

Methods (1)

Keywords

active learning (10) regret bound (9) online learning (8) label complexity (8) contextual bandit (4) multi-armed bandit (4) continuous action (3) multi-task learning (3) supervised learning (2) online algorithm (2) bandit algorithm (2) halfspace classifier (2) multiclass classification (2) upper confidence bound (2) tsybakov noise (2) pac learning (2) sample complexity (2) bandit feedback (2) thompson sampling (2) sparse halfspace (2)

Papers

Towards Fundamental Limits for Active Multi-distribution Learning COLT 2025
The Human-AI Substitution game: active learning from a strategic labeler ICLR 2024
Beyond task diversity: provable representation transfer for sequential multitask linear bandits NIPS 2024
Efficient Active Learning Halfspaces with Tsybakov Noise: A Non-convex Optimization Approach AISTATS 2024
Agnostic Interactive Imitation Learning: New Theory and Practical Algorithms ICML 2024
Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank Bandits ICML 2024
Kullback-Leibler Maillard Sampling for Multi-armed Bandits with Bounded Rewards NIPS 2023
Active fairness auditing ICML 2022
Thompson Sampling for Robust Transfer in Multi-Task Bandits ICML 2022
Margin-distancing for safe model explanation AISTATS 2022
PopArt: Efficient Sparse Regression and Experimental Design for Optimal Sparse Linear Bandits NIPS 2022
On Efficient Online Imitation Learning via Classification NIPS 2022
Provably efficient multi-task reinforcement learning with model transfer NIPS 2021
Improved Algorithms for Efficient Active Learning Halfspaces with Massart and Tsybakov Noise COLT 2021
Attribute-Efficient Learning of Halfspaces with Malicious Noise: Near-Optimal Label Complexity and Noise Tolerance ALT 2021
Multitask Bandit Learning Through Heterogeneous Feedback Aggregation AISTATS 2021
Active Online Learning with Hidden Shifting Domains AISTATS 2021
Contextual Bandits with Continuous Actions: Smoothing, Zooming, and Adapting JMLR 2020
Efficient Contextual Bandits with Continuous Actions NIPS 2020
Crush Optimism with Pessimism: Structured Bandits Beyond Asymptotic Optimality NIPS 2020
Efficient active learning of sparse halfspaces with arbitrary bounded noise NIPS 2020
Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds ICLR 2020
Contextual bandits with continuous actions: Smoothing, zooming, and adapting COLT 2019
Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case ICML 2019
Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback ICML 2019
Efficient active learning of sparse halfspaces COLT 2018
Revisiting Perceptron: Efficient and Label-Optimal Learning of Halfspaces NIPS 2017
Efficient Online Bandit Multiclass Learning with $\tilde{O}(\sqrt{T})$ Regret ICML 2017
The Extended Littlestone’s Dimension for Learning with Mistakes and Abstentions COLT 2016
Search Improves Label for Active Learning NIPS 2016
Active Learning from Weak and Strong Labelers NIPS 2015
Spectral Learning of Large Structured HMMs for Comparative Epigenomics NIPS 2015
Beyond Disagreement-Based Agnostic Active Learning NIPS 2014