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Roie Reshef

2 accepted papers

2025

Privacy-Preserving Federated Convex Optimization: Balancing Partial-Participation and Efficiency via Noise Cancellation

ICML 2025poster

This paper addresses the challenge of achieving Differential Privacy (DP) in Federated Learning (FL) under the partial-participation setting, where each machine participates in only some of training rounds. While earlier work achieved optimal performance and efficiency in full-participation scenario…

Cited by 0SourcePDFScholar
2024

Private and Federated Stochastic Convex Optimization: Efficient Strategies for Centralized Systems

ICML 2024poster

This paper addresses the challenge of preserving privacy in Federated Learning (FL) within centralized systems, focusing on both trusted and untrusted server scenarios. We analyze this setting within the Stochastic Convex Optimization (SCO) framework, and devise methods that ensure Differential Priv…

Cited by 0SourcePDFScholar