Search Results for author: Chi-Hua Wang

Found 11 papers, 0 papers with code

On the Utility Recovery Incapability of Neural Net-based Differential Private Tabular Training Data Synthesizer under Privacy Deregulation

no code implementations28 Nov 2022 Yucong Liu, Chi-Hua Wang, Guang Cheng

Devising procedures for auditing generative model privacy-utility tradeoff is an important yet unresolved problem in practice.

Always Valid Risk Monitoring for Online Matrix Completion

no code implementations18 Nov 2022 Chi-Hua Wang, Wenjie Li

Always-valid concentration inequalities are increasingly used as performance measures for online statistical learning, notably in the learning of generative models and supervised learning.

Matrix Completion online learning

Non-Stationary Dynamic Pricing Via Actor-Critic Information-Directed Pricing

no code implementations19 Aug 2022 Po-Yi Liu, Chi-Hua Wang, Henghsiu Tsai

This paper presents a novel non-stationary dynamic pricing algorithm design, where pricing agents face incomplete demand information and market environment shifts.

Thompson Sampling

Rate-Optimal Contextual Online Matching Bandit

no code implementations7 May 2022 Yuantong Li, Chi-Hua Wang, Guang Cheng, Will Wei Sun

Existing works focus on multi-armed bandit with static preference, but this is insufficient: the two-sided preference changes as along as one-side's contextual information updates, resulting in non-static matching.

Federated Online Sparse Decision Making

no code implementations27 Feb 2022 Chi-Hua Wang, Wenjie Li, Guang Cheng, Guang Lin

This paper presents a novel federated linear contextual bandits model, where individual clients face different K-armed stochastic bandits with high-dimensional decision context and coupled through common global parameters.

Decision Making Multi-Armed Bandits

Residual Bootstrap Exploration for Stochastic Linear Bandit

no code implementations23 Feb 2022 Shuang Wu, Chi-Hua Wang, Yuantong Li, Guang Cheng

We propose a new bootstrap-based online algorithm for stochastic linear bandit problems.

Optimum-statistical Collaboration Towards General and Efficient Black-box Optimization

no code implementations17 Jun 2021 Wenjie Li, Chi-Hua Wang, Qifan Song, Guang Cheng

In this paper, we make the key delineation on the roles of resolution and statistical uncertainty in hierarchical bandits-based black-box optimization algorithms, guiding a more general analysis and a more efficient algorithm design.

Online Forgetting Process for Linear Regression Models

no code implementations3 Dec 2020 Yuantong Li, Chi-Hua Wang, Guang Cheng

Motivated by the EU's "Right To Be Forgotten" regulation, we initiate a study of statistical data deletion problems where users' data are accessible only for a limited period of time.

regression

Online Regularization towards Always-Valid High-Dimensional Dynamic Pricing

no code implementations5 Jul 2020 Chi-Hua Wang, Zhanyu Wang, Will Wei Sun, Guang Cheng

In this paper, we propose a novel approach for designing dynamic pricing policy based regularized online statistical learning with theoretical guarantees.

Online Batch Decision-Making with High-Dimensional Covariates

no code implementations21 Feb 2020 Chi-Hua Wang, Guang Cheng

In such a scenario, our goal is to allocate a batch of treatments to maximize treatment efficacy based on observed high-dimensional user covariates.

Decision Making Marketing

Residual Bootstrap Exploration for Bandit Algorithms

no code implementations19 Feb 2020 Chi-Hua Wang, Yang Yu, Botao Hao, Guang Cheng

In this paper, we propose a novel perturbation-based exploration method in bandit algorithms with bounded or unbounded rewards, called residual bootstrap exploration (\texttt{ReBoot}).

Multi-Armed Bandits Thompson Sampling

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