Huazheng Wang | DeepAI

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Featured Co-authors

Wei Chen
332 publications
Jianfeng Gao
241 publications
Dinesh Manocha
230 publications
Zhiyuan Liu
209 publications
Jing Wang
124 publications
Csaba Szepesvari
116 publications
Zhuoran Yang
110 publications
Zhe Gan
102 publications
Yu Wu
98 publications
Tuo Zhao
94 publications
Mengdi Wang
91 publications

∙ 08/03/2023

Aligning Agent Policy with Externalities: Reward Design via Bilevel RL

In reinforcement learning (RL), a reward function is often assumed at th...

0 Souradip Chakraborty, et al. ∙

∙ 07/26/2023

Online Modeling and Monitoring of Dependent Processes under Resource Constraints

Monitoring a population of dependent processes under limited resources i...

0 Tanapol Kosolwattana, et al. ∙

∙ 07/26/2023

How Does Diffusion Influence Pretrained Language Models on Out-of-Distribution Data?

Transformer-based pretrained language models (PLMs) have achieved great ...

0 Huazheng Wang, et al. ∙

∙ 07/24/2023

Provable Benefits of Policy Learning from Human Preferences in Contextual Bandit Problems

A crucial task in decision-making problems is reward engineering. It is ...

0 Xiang Ji, et al. ∙

∙ 06/21/2023

Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP

In this paper, we study representation learning in partially observable ...

0 Jiacheng Guo, et al. ∙

∙ 06/13/2023

Unified Off-Policy Learning to Rank: a Reinforcement Learning Perspective

Off-policy Learning to Rank (LTR) aims to optimize a ranker from data co...

7 Zeyu Zhang, et al. ∙

∙ 05/30/2023

Adversarial Attacks on Online Learning to Rank with Stochastic Click Models

We propose the first study of adversarial attacks on online learning to ...

0 Zichen Wang, et al. ∙

∙ 02/08/2023

Machine Learning for Synthetic Data Generation: a Review

Data plays a crucial role in machine learning. However, in real-world ap...

0 Yingzhou Lu, et al. ∙

∙ 08/30/2022

Dynamic Global Sensitivity for Differentially Private Contextual Bandits

Bandit algorithms have become a reference solution for interactive recom...

0 Huazheng Wang, et al. ∙

∙ 06/29/2022

Provably Efficient Reinforcement Learning for Online Adaptive Influence Maximization

Online influence maximization aims to maximize the influence spread of a...

3 Kaixuan Huang, et al. ∙

∙ 06/10/2022

Communication Efficient Distributed Learning for Kernelized Contextual Bandits

We tackle the communication efficiency challenge of learning kernelized ...

0 Chuanhao Li, et al. ∙

∙ 06/05/2022

Bandit Theory and Thompson Sampling-Guided Directed Evolution for Sequence Optimization

Directed Evolution (DE), a landmark wet-lab method originated in 1960s, ...

0 Hui Yuan, et al. ∙

∙ 10/18/2021

When Are Linear Stochastic Bandits Attackable?

We study adversarial attacks on linear stochastic bandits, a sequential ...

0 Huazheng Wang, et al. ∙

∙ 04/08/2021

Incentivizing Exploration in Linear Bandits under Information Gap

We study the problem of incentivizing exploration for myopic users in li...

0 Huazheng Wang, et al. ∙

∙ 02/28/2021

PairRank: Online Pairwise Learning to Rank by Divide-and-Conquer

Online Learning to Rank (OL2R) eliminates the need of explicit relevance...

0 Yiling Jia, et al. ∙

∙ 07/16/2020

A Smoothed Analysis of Online Lasso for the Sparse Linear Contextual Bandit Problem

We investigate the sparse linear contextual bandit problem where the par...

0 Zhiyuan Liu, et al. ∙

∙ 04/28/2020

Unbiased Learning to Rank: Online or Offline?

How to obtain an unbiased ranking model by learning to rank with biased ...

0 Qingyao Ai, et al. ∙

∙ 11/12/2019

Incentivized Exploration for Multi-Armed Bandits under Reward Drift

We study incentivized exploration for the multi-armed bandit (MAB) probl...

0 Zhiyuan Liu, et al. ∙

∙ 08/24/2019

Adversarial Domain Adaptation for Machine Reading Comprehension

In this paper, we focus on unsupervised domain adaptation for Machine Re...

0 Huazheng Wang, et al. ∙

∙ 06/10/2019

Variance Reduction in Gradient Exploration for Online Learning to Rank

Online Learning to Rank (OL2R) algorithms learn from implicit user feedb...

0 Huazheng Wang, et al. ∙

∙ 06/09/2019

Factorization Bandits for Online Influence Maximization

We study the problem of online influence maximization in social networks...

0 Qingyun Wu, et al. ∙

∙ 05/18/2018

Efficient Exploration of Gradient Space for Online Learning to Rank

Online learning to rank (OL2R) optimizes the utility of returned search ...

0 Huazheng Wang, et al. ∙

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