Global ETD Search

Differentially private online learning algorithms for federated optimization

Odeyomi, Olusola T.2021

wichita-thes

Toward communication-efficient and secure distributed machine learning

Xie, CongUniversity of Illinois at Urbana-Champaign2021

… SGD, to reduce the communication overhead; 2) federated optimization in asynchronous mode; 3) a framework of score-based approaches for Byzantine tolerance in distributed SGD; 4) a distributed learning system integrating all these three techniques. The proposed system provides communication …

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On Principles of Efficiency for Federated Learning

Qiu, XinchiUniversity of Cambridge2025

… edge computing technologies. In this landscape, Federated Learning (FL) has emerged as a crucial machine learning paradigm that enables collaborative model training across various institutions or devices, crucially preserving the privacy of raw and sensitive data. This approach is particularly …

cambridge Repository record for On Principles of Efficiency for Federated Learning (opens in a new tab)

Foundations of Multiple-Time-Scale Stochastic Approximation for Fast and Resilient Distributed Optimization Algorithms

Dutta, AmitVirginia Tech2025

… and designing fast and resilient distributed optimization algorithms for large-scale networks. The central focus is on understanding and leveraging two-time-scale dynamics, which may arise naturally from the underlying network structure or be introduced through algorithmic design. Motivated by …

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