4 citations · 13 across the 7 of their papers we have counts for
7 papers
Two-sided Competing Matching Recommendation Markets With Quota and Complementary Preferences Constraints
Yuantong Li, Guang Cheng, Xiaowu Dai
In this paper, we propose a new recommendation algorithm for addressing the problem of two-sided online matching markets with complementary preferences and quota constraints, where…
On the Utility Recovery Incapability of Neural Net-based Differential Private Tabular Training Data Synthesizer under Privacy Deregulation
Yucong Liu, Chi-Hua Wang, Guang Cheng
Devising procedures for auditing generative model privacy-utility tradeoff is an important yet unresolved problem in practice. Existing works concentrates on investigating the priv…
Dynamic Matching Bandit For Two-Sided Online Markets
Yuantong Li, Chi-hua Wang, Guang Cheng +1
Two-sided online matching platforms are employed in various markets. However, agents' preferences in the current market are usually implicit and unknown, thus needing to be learned…
Federated Online Sparse Decision Making
Chi-Hua Wang, Wenjie Li, Guang Cheng +1
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…
Residual Bootstrap Exploration for Stochastic Linear Bandit
Shuang Wu, Chi-Hua Wang, Yuantong Li +1
We propose a new bootstrap-based online algorithm for stochastic linear bandit problems. The key idea is to adopt residual bootstrap exploration, in which the agent estimates the n…
Optimum-statistical Collaboration Towards General and Efficient Black-box Optimization
Wenjie Li, Chi-Hua Wang, Guang Cheng +1
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 ge…
Variance Reduction on General Adaptive Stochastic Mirror Descent
Wenjie Li, Zhanyu Wang, Yichen Zhang +1
In this work, we investigate the idea of variance reduction by studying its properties with general adaptive mirror descent algorithms in nonsmooth nonconvex finite-sum optimizatio…