31 citations · 31 across the 2 of their papers we have counts for
5 papers
Data Overvaluation Attack and Truthful Data Valuation in Federated Learning
Shuyuan Zheng, Sudong Cai, Chuan Xiao +4
In collaborative machine learning (CML), data valuation, i.e., evaluating the contribution of each client's data to the machine learning model, has become a critical task for incen…
Secure Shapley Value for Cross-Silo Federated Learning (Technical Report)
Shuyuan Zheng, Yang Cao, Masatoshi Yoshikawa
The Shapley value (SV) is a fair and principled metric for contribution evaluation in cross-silo federated learning (cross-silo FL), wherein organizations, i.e., clients, collabora…
FL-Market: Trading Private Models in Federated Learning
Shuyuan Zheng, Yang Cao, Masatoshi Yoshikawa +2
The difficulty in acquiring a sufficient amount of training data is a major bottleneck for machine learning (ML) based data analytics. Recently, commoditizing ML models has been pr…
Pricing Private Data with Personalized Differential Privacy and Partial Arbitrage Freeness
Shuyuan Zheng, Yang Cao, Masatoshi Yoshikawa
There is a growing trend regarding perceiving personal data as a commodity. Existing studies have built frameworks and theories about how to determine an arbitrage-free price of a…
Trading Location Data with Bounded Personalized Privacy Loss
Shuyuan Zheng, Yang Cao, Masatoshi Yoshikawa
As personal data have been the new oil of the digital era, there is a growing trend perceiving personal data as a commodity. Although some people are willing to trade their persona…