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Exact worst-case convergence rates of gradient descent: a complete analysis for all constant stepsizes over nonconvex and convex functions
T Rotaru, F Glineur, P Patrinos - ar** their graph onto the complex plane. In this work, we study the SRG of …
iFedDR: Auto-Tuning Local Computation with Inexact Douglas-Rachford Splitting in Federated Learning
Federated learning usually requires specifying the amount of local computation needed a
priori. In this work, we instead propose a systematic scheme to automatically adjust and …
priori. In this work, we instead propose a systematic scheme to automatically adjust and …
On the convergence of warped proximal iterations for solving nonmonotone inclusions and applications
D Papadimitriou, BC Vu - OPT 2023: Optimization for Machine Learning - openreview.net
In machine learning, tackling fairness, robustness, and safeness requires to solve
nonconvex optimization problems with various constraints. In this paper, we investigate the …
nonconvex optimization problems with various constraints. In this paper, we investigate the …