no code implementations • 31 May 2023 • Yige Hong, Qiaomin Xie, Yudong Chen, Weina Wang
In both settings, we establish the first asymptotic optimality result that does not require UGAP.
no code implementations • 25 May 2023 • Honghao Wei, Xin Liu, Weina Wang, Lei Ying
This method significantly improves learning by reducing the sample complexity such that the dataset only needs to have sufficient coverage of the stochastic states.
no code implementations • 8 Jun 2021 • Tuhinangshu Choudhury, Gauri Joshi, Weina Wang, Sanjay Shakkottai
In multi-server queueing systems where there is no central queue holding all incoming jobs, job dispatching policies are used to assign incoming jobs to the queue at one of the servers.
no code implementations • 29 Jun 2020 • Wenxin Ding, Nihar B. Shah, Weina Wang
The crux of the framework lies in recognizing that a part of the data pertaining to the reviews is already available in public, and we use this information to post-process the data released by any privacy mechanism in a manner that improves the accuracy (utility) of the data while retaining the privacy guarantees.
no code implementations • 4 Mar 2019 • Honghao Wei, Xiaohan Kang, Weina Wang, Lei Ying
The algorithm consists of an offline machine learning algorithm for learning the probabilistic information spreading model and an online optimal stopping algorithm to detect misinformation.
no code implementations • 25 Jan 2019 • Harsh Gupta, Seo Taek Kong, R. Srikant, Weina Wang
In this paper, we show that a simple modification to Boltzmann exploration, motivated by a variation of the standard doubling trick, achieves $O(K\log^{1+\alpha} T)$ regret for a stochastic MAB problem with $K$ arms, where $\alpha>0$ is a parameter of the algorithm.