Chicheng Zhang

research

∙ 06/17/2022

Thompson Sampling for Robust Transfer in Multi-Task Bandits

We study the problem of online multi-task learning where the tasks are p...

Zhi Wang, et al. ∙

research

∙ 06/16/2022

Active Fairness Auditing

The fast spreading adoption of machine learning (ML) by companies across...

Tom Yan, et al. ∙

research

∙ 02/23/2022

Margin-distancing for safe model explanation

The growing use of machine learning models in consequential settings has...

Tom Yan, et al. ∙

research

∙ 10/28/2021

SIM-ECG: A Signal Importance Mask-driven ECGClassification System

Heart disease is the number one killer, and ECGs can assist in the early...

Dharma KC, et al. ∙

research

∙ 07/19/2021

Provably Efficient Multi-Task Reinforcement Learning with Model Transfer

We study multi-task reinforcement learning (RL) in tabular episodic Mark...

Chicheng Zhang, et al. ∙

research

∙ 02/10/2021

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

We develop a computationally-efficient PAC active learning algorithm for...

Chicheng Zhang, et al. ∙

research

∙ 10/29/2020

Multitask Bandit Learning through Heterogeneous Feedback Aggregation

In many real-world applications, multiple agents seek to learn how to pe...

Zhi Wang, et al. ∙

research

∙ 06/25/2020

Active Online Domain Adaptation

Online machine learning systems need to adapt to domain shifts. Meanwhil...

Yining Chen, et al. ∙

research

∙ 06/15/2020

Crush Optimism with Pessimism: Structured Bandits Beyond Asymptotic Optimality

We study stochastic structured bandits for minimizing regret. The fact t...

Kwang-Sung Jun, et al. ∙

research

∙ 06/10/2020

Efficient Contextual Bandits with Continuous Actions

We create a computationally tractable algorithm for contextual bandits w...

Maryam Majzoubi, et al. ∙

research

∙ 06/06/2020

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

This paper is concerned with computationally efficient learning of homog...

Jie Shen, et al. ∙

research

∙ 02/12/2020

Efficient active learning of sparse halfspaces with arbitrary bounded noise

In this work we study active learning of homogeneous s-sparse halfspaces...

Chicheng Zhang, et al. ∙

research

∙ 06/09/2019

Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds

We design a new algorithm for batch active learning with deep neural net...

Jordan T. Ash, et al. ∙

research

∙ 02/06/2019

Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case

We study the problem of efficient online multiclass linear classificatio...

Alina Beygelzimer, et al. ∙

research

∙ 02/05/2019

Contextual Bandits with Continuous Actions: Smoothing, Zooming, and Adapting

We study contextual bandit learning with an abstract policy class and co...

Akshay Krishnamurthy, et al. ∙

research

∙ 01/02/2019

Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback

We investigate the feasibility of learning from both fully-labeled super...

Chicheng Zhang, et al. ∙

research

∙ 05/07/2018

Efficient active learning of sparse halfspaces

We study the problem of efficient PAC active learning of homogeneous lin...

Chicheng Zhang, et al. ∙

research

∙ 02/07/2018

Spectral Learning of Binomial HMMs for DNA Methylation Data

We consider learning parameters of Binomial Hidden Markov Models, which ...

Chicheng Zhang, et al. ∙

research

∙ 02/25/2017

Efficient Online Bandit Multiclass Learning with Õ(√(T)) Regret

We present an efficient second-order algorithm with Õ(1/η√(T)) regret fo...

Alina Beygelzimer, et al. ∙

research

∙ 02/18/2017

Revisiting Perceptron: Efficient and Label-Optimal Learning of Halfspaces

It has been a long-standing problem to efficiently learn a halfspace usi...

Songbai Yan, et al. ∙

research

∙ 02/23/2016

Search Improves Label for Active Learning

We investigate active learning with access to two distinct oracles: Labe...

Alina Beygelzimer, et al. ∙

research

∙ 10/09/2015

Active Learning from Weak and Strong Labelers

An active learner is given a hypothesis class, a large set of unlabeled ...

Chicheng Zhang, et al. ∙

research

∙ 06/04/2015

Spectral Learning of Large Structured HMMs for Comparative Epigenomics

We develop a latent variable model and an efficient spectral algorithm m...

Chicheng Zhang, et al. ∙

research

∙ 07/10/2014

Beyond Disagreement-based Agnostic Active Learning

We study agnostic active learning, where the goal is to learn a classifi...

Chicheng Zhang, et al. ∙

Chicheng Zhang

Featured Co-authors

Tengyu Ma

Daniel Hsu

Akshay Krishnamurthy

Kamalika Chaudhuri

Zhi Wang

Alekh Agarwal

Jie Shen

John Langford

Haipeng Luo

Hal Daumé III

Pranjal Awasthi

Thompson Sampling for Robust Transfer in Multi-Task Bandits

Active Fairness Auditing

Margin-distancing for safe model explanation

SIM-ECG: A Signal Importance Mask-driven ECGClassification System

Provably Efficient Multi-Task Reinforcement Learning with Model Transfer

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

Multitask Bandit Learning through Heterogeneous Feedback Aggregation

Active Online Domain Adaptation

Crush Optimism with Pessimism: Structured Bandits Beyond Asymptotic Optimality

Efficient Contextual Bandits with Continuous Actions

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

Efficient active learning of sparse halfspaces with arbitrary bounded noise

Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds

Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case

Contextual Bandits with Continuous Actions: Smoothing, Zooming, and Adapting

Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback

Efficient active learning of sparse halfspaces

Spectral Learning of Binomial HMMs for DNA Methylation Data

Efficient Online Bandit Multiclass Learning with Õ(√(T)) Regret

Revisiting Perceptron: Efficient and Label-Optimal Learning of Halfspaces

Search Improves Label for Active Learning

Active Learning from Weak and Strong Labelers

Spectral Learning of Large Structured HMMs for Comparative Epigenomics

Beyond Disagreement-based Agnostic Active Learning