1 citations · 1 across the 7 of their papers we have counts for
7 papers
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…
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…
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…
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…
Sales Policies for a Virtual Assistant
Wenjia Ba, Haim Mendelson, Mingxi Zhu
We study the implications of selling through a voice-based virtual assistant (VA). The seller has a set of products available and the VA decides which product to offer and at what…
On a Randomized Multi-Block ADMM for Solving Selected Machine Learning Problems
Mingxi Zhu, Kresimir Mihic, Yinyu Ye
The Alternating Direction Method of Multipliers (ADMM) has now days gained tremendous attentions for solving large-scale machine learning and signal processing problems due to the…
Managing Randomization in the Multi-Block Alternating Direction Method of Multipliers for Quadratic Optimization
Kresimir Mihic, Mingxi Zhu, Yinyu Ye
The Alternating Direction Method of Multipliers (ADMM) has gained a lot of attention for solving large-scale and objective-separable constrained optimization. However, the two-bloc…