4 citations · 8 across the 7 of their papers we have counts for
7 papers
Performative Prediction with Bandit Feedback: Learning through Reparameterization
Yatong Chen, Wei Tang, Chien-Ju Ho +1
Performative prediction, as introduced by Perdomo et al, is a framework for studying social prediction in which the data distribution itself changes in response to the deployment o…
Dynamic Pricing and Advertising with Demand Learning
Shipra Agrawal, Yiding Feng, Wei Tang
We consider a novel pricing and advertising framework in which a seller not only sets the product price but also designs flexible advertising schemes to influence customers' valuat…
Rationality-Robust Information Design: Bayesian Persuasion under Quantal Response
Yiding Feng, Chien-Ju Ho, Wei Tang
Classic mechanism/information design imposes the assumption that agents are fully rational, meaning each of them always selects the action that maximizes her expected utility. Yet…
No-Regret Bayesian Recommendation to Homogeneous Users
Yiding Feng, Wei Tang, Haifeng Xu
We introduce and study the online Bayesian recommendation problem for a recommender system platform. The platform has the privilege to privately observe a utility-relevant \emph{st…
Optimal Query Complexity of Secure Stochastic Convex Optimization
Wei Tang, Chien-Ju Ho, Yang Liu
We study the secure stochastic convex optimization problem. A learner aims to learn the optimal point of a convex function through sequentially querying a (stochastic) gradient ora…
Competitive Information Design for Pandora's Box
Bolin Ding, Yiding Feng, Chien-Ju Ho +2
We study a natural competitive-information-design strategic variant for the celebrated Pandora's Box problem (Weitzman, 1979), where each box is associated with a strategic informa…
Bandit Learning with Delayed Impact of Actions
Wei Tang, Chien-Ju Ho, Yang Liu
We consider a stochastic multi-armed bandit (MAB) problem with delayed impact of actions. In our setting, actions taken in the past impact the arm rewards in the subsequent future.…