274 citations · 480 across the 29 of their papers we have counts for
6 papers · 1 filter
Multitask Bandit Learning Through Heterogeneous Feedback Aggregation
Zhi Wang, Chicheng Zhang, Manish Kumar Singh +2
In many real-world applications, multiple agents seek to learn how to perform highly related yet slightly different tasks in an online bandit learning protocol. We formulate this p…
Active Online Learning with Hidden Shifting Domains
Yining Chen, Haipeng Luo, Tengyu Ma +1
Online machine learning systems need to adapt to domain shifts. Meanwhile, acquiring label at every timestep is expensive. We propose a surprisingly simple algorithm that adaptivel…
Crush Optimism with Pessimism: Structured Bandits Beyond Asymptotic Optimality
Kwang-Sung Jun, Chicheng Zhang
We study stochastic structured bandits for minimizing regret. The fact that the popular optimistic algorithms do not achieve the asymptotic instance-dependent regret optimality (as…
Efficient Contextual Bandits with Continuous Actions
Maryam Majzoubi, Chicheng Zhang, Rajan Chari +3
We create a computationally tractable algorithm for contextual bandits with continuous actions having unknown structure. Our reduction-style algorithm composes with most supervised…
Attribute-Efficient Learning of Halfspaces with Malicious Noise: Near-Optimal Label Complexity and Noise Tolerance
Jie Shen, Chicheng Zhang
This paper is concerned with computationally efficient learning of homogeneous sparse halfspaces in under noise. Though recent works have established attribute-effic…
Efficient active learning of sparse halfspaces with arbitrary bounded noise
Chicheng Zhang, Jie Shen, Pranjal Awasthi
We study active learning of homogeneous -sparse halfspaces in under the setting where the unlabeled data distribution is isotropic log-concave and each label is f…