13 citations · 26 across the 7 of their papers we have counts for
7 papers · 1 filter
A Definition of Non-Stationary Bandits
Yueyang Liu, Xu Kuang, Benjamin Van Roy
Despite the subject of non-stationary bandit learning having attracted much recent attention, we have yet to identify a formal definition of non-stationarity that can consistently…
Non-Stationary Bandit Learning via Predictive Sampling
Yueyang Liu, Xu Kuang, Benjamin Van Roy
Thompson sampling has proven effective across a wide range of stationary bandit environments. However, as we demonstrate in this paper, it can perform poorly when applied to non-st…
Gaussian Imagination in Bandit Learning
Yueyang Liu, Adithya M. Devraj, Benjamin Van Roy +1
Assuming distributions are Gaussian often facilitates computations that are otherwise intractable. We study the performance of an agent that attains a bounded information ratio wit…
Learning and Information in Stochastic Networks and Queues
Neil Walton, Kuang Xu
We review the role of information and learning in the stability and optimization of queueing systems. In recent years, techniques from supervised learning, bandit learning and rein…
A Bit Better? Quantifying Information for Bandit Learning
Adithya M. Devraj, Benjamin Van Roy, Kuang Xu
The information ratio offers an approach to assessing the efficacy with which an agent balances between exploration and exploitation. Originally, this was defined to be the ratio b…
Query Complexity of Bayesian Private Learning
Kuang Xu
We study the query complexity of Bayesian Private Learning: a learner wishes to locate a random target within an interval by submitting queries, in the presence of an adversary who…