Events

CDS Seminar: Digital Privacy in Personalized Pricing and Trustworthy Machine Learning via Blockchain

Speaker: Xi Chen

Location: 60 Fifth Avenue, Room 150

Date: Friday, February 14, 2025

This talk has two parts. The first part is on digital privacy in personalized pricing. When involving personalized information, how to protect the privacy of such information becomes a critical issue in practice. In this talk, we consider a dynamic pricing problem with an unknown demand function of posted prices and personalized information. By leveraging the fundamental framework of differential privacy, we develop a privacy-preserving dynamic pricing policy, which tries to maximize the retailer revenue while avoiding information leakage of individual customers' information and purchasing decisions. This is joint work with Prof. Yining Wang and Prof. David Simchi-Levi. The second part introduces the concept of using blockchain to create a decentralized computing market for any AI training/fine-tuning. We introduce the concept of incentive-security that incentivizes rational trainers to behave honestly for their best interest. We design a Proof-of-Learning mechanism with computational efficiency, a provable incentive-security guarantee, and controllable difficulty.  Our research also proposes an environmentally friendly verification mechanism for blockchain systems, allowing existing proof-of-work computations to be used for AI services, thus achieving useful proof-of-work.