5 citations · 16 across the 15 of their papers we have counts for
6 papers · 1 filter
Uncertainty-Aware Instance Reweighting for Off-Policy Learning
Xiaoying Zhang, Junpu Chen, Hongning Wang +4
Off-policy learning, referring to the procedure of policy optimization with access only to logged feedback data, has shown importance in various real-world applications, such as se…
Multiple-Play Stochastic Bandits with Shareable Finite-Capacity Arms
Xuchuang Wang, Hong Xie, John C. S. Lui
We generalize the multiple-play multi-armed bandits (MP-MAB) problem with a shareable arm setting, in which several plays can share the same arm. Furthermore, each shareable arm ha…
LPC-AD: Fast and Accurate Multivariate Time Series Anomaly Detection via Latent Predictive Coding
Zhi Qi, Hong Xie, Ye Li +3
This paper proposes LPC-AD, a fast and accurate multivariate time series (MTS) anomaly detection method. LPC-AD is motivated by the ever-increasing needs for fast and accurate MTS…
Multi-Player Multi-Armed Bandits with Finite Shareable Resources Arms: Learning Algorithms & Applications
Xuchuang Wang, Hong Xie, John C. S. Lui
Multi-player multi-armed bandits (MMAB) study how decentralized players cooperatively play the same multi-armed bandit so as to maximize their total cumulative rewards. Existing MM…
Combining Offline Causal Inference and Online Bandit Learning for Data Driven Decision
Li Ye, Yishi Lin, Hong Xie +1
A fundamental question for companies with large amount of logged data is: How to use such logged data together with incoming streaming data to make good decisions? Many companies c…
Conversational Contextual Bandit: Algorithm and Application
Xiaoying Zhang, Hong Xie, Hang Li +1
Contextual bandit algorithms provide principled online learning solutions to balance the exploitation-exploration trade-off in various applications such as recommender systems. How…