4 papers
Mechanism for Collaborative Federated Learning: Pitfalls of Shapley Values
Meng Qi, Mingxi Zhu
This paper investigates the impact of mechanism design on collaborative learning systems enabled by federated learning (FL). We propose a multi-action collaborative federated learn…
Learning by Doing: The Case of Online Lending
Mendelson Haim, Zhu Mingxi
Online lending, a phenomenon which is becoming mainstream due to the migration of consumer finance to the Internet and the adoption of AI based lending models, is an example of lea…
How a Small Amount of Data Sharing Benefits Distributed Optimization and Learning : The Upside of Data Heterogeneity
Mingxi Zhu, Yinyu Ye
Distributed optimization algorithms are widely used in machine learning. This paper investigates how a small amount of data sharing can improve their performance. Focusing on gener…
Design Information Disclosure under Bidder Heterogeneity in Online Advertising Auctions: Implications of Bid-Adherence Behavior
Zhu Mingxi, Song Michelle
Bidding is a key element of search advertising, but the variation in bidders' valuations and strategies is often overlooked. Disclosing bid information helps uncover this heterogen…