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Picture of Chicheng Zhang

Chicheng Zhang

Member of the Graduate Faculty | Assistant Professor, Computer Science

Computer Science

Collaboration(19)

Hao Zhang
Rongguang Liang
Ruth Taylor-Piliae
Larry Head
Michael Chertkov

Page 1 of 4

Research Opportunities(1)

Undergrad Research Opp Volunteer, For Credit
Prerequisite Courses: undergraduate probability and statistics, basic programming, algorithm design Majors: Computer science, data science, math, physics, statistics

Grants(1)

Publications(21)

Recent

Active Online Learning with Hidden Shifting Domains

2021

active learning, domain adaptation, online learning, hidden domains, machine learning

Improved Algorithms for Efficient Active Learning Halfspaces with Massart and Tsybakov noise

2021

machine learning, algorithm, active learning, noise, efficiency

Provably Efficient Multi-Task Reinforcement Learning with Model Transfer

2021

reinforcement learning, model transfer, multi-task learning, efficient learning, provably efficient learning

Multitask Bandit Learning Through Heterogeneous Feedback Aggregation

2021

multi-armed bandits, reinforcement learning, feedback aggregation, multi-task learning, heterogeneous data

Attribute-Efficient Learning of Halfspaces with Malicious Noise: Near-Optimal Label Complexity and Noise Tolerance

2021

machine learning, robustness, noise tolerance, data privacy, optimization

Crush Optimism with Pessimism: Structured Bandits Beyond Asymptotic Optimality.

2020

bandit algorithms, optimization, decision making, machine learning, algorithmic theory

DeeBatch Active Learning by Diverse, Uncertain Gradient Lower Bounds

2020

machine learning, data analysis, optimization, algorithms, artificial intelligence

Efficient active learning of sparse halfspaces with arbitrary bounded noise

2020

active learning, sparse data, halfspaces, noise bound, efficiency

Efficient Contextual Bandits with Continuous Actions

2020

reinforcement learning, decision making, optimization, machine learning, artificial intelligence

Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case

2019

multiclass classification, linear models, efficient algorithms, bandit algorithms, machine learning