438 citations · 1k across the 57 of their papers we have counts for
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Dynamic Privacy Allocation for Locally Differentially Private Federated Learning with Composite Objectives
Jiaojiao Zhang, Dominik Fay, Mikael Johansson
This paper proposes a locally differentially private federated learning algorithm for strongly convex but possibly nonsmooth problems that protects the gradients of each worker aga…
Delay-agnostic Asynchronous Coordinate Update Algorithm
Xuyang Wu, Changxin Liu, Sindri Magnusson +1
We propose a delay-agnostic asynchronous coordinate update algorithm (DEGAS) for computing operator fixed points, with applications to asynchronous optimization. DEGAS includes nov…
Generalized Polyak Step Size for First Order Optimization with Momentum
Xiaoyu Wang, Mikael Johansson, Tong Zhang
In machine learning applications, it is well known that carefully designed learning rate (step size) schedules can significantly improve the convergence of commonly used first-orde…
Delay-agnostic Asynchronous Distributed Optimization
Xuyang Wu, Changxin Liu, Sindri Magnusson +1
Existing asynchronous distributed optimization algorithms often use diminishing step-sizes that cause slow practical convergence, or fixed step-sizes that depend on an assumed uppe…