460 citations · 535 across the 16 of their papers we have counts for
Showing 2021Show all
3 papers · 1 filter
cs.IR2021★ 6 cited
Practical and Secure Federated Recommendation with Personalized Masks
Liu Yang, Junxue Zhang, Di Chai +4
Federated recommendation addresses the data silo and privacy problems altogether for recommender systems. Current federated recommender systems mainly utilize cryptographic or obfu…
cs.CR2021★ 3 cited
Aegis: A Trusted, Automatic and Accurate Verification Framework for Vertical Federated Learning
Cengguang Zhang, Junxue Zhang, Di Chai +1
Vertical federated learning (VFL) leverages various privacy-preserving algorithms, e.g., homomorphic encryption or secret sharing based SecureBoost, to ensure data privacy. However…
cs.DC2021
Practical Lossless Federated Singular Vector Decomposition over Billion-Scale Data
Di Chai, Leye Wang, Junxue Zhang +4
With the enactment of privacy-preserving regulations, e.g., GDPR, federated SVD is proposed to enable SVD-based applications over different data sources without revealing the origi…