Publications associées à Federated Learning Over Wireless Networks: Convergence Analysis and Resource Allocation

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A first-order primal-dual method with adaptivity to local smoothness

Volkan Cevher, Maria-Luiza Vladarean

We consider the problem of finding a saddle point for the convex-concave objective

\min_x \max_y f(x) + \langle Ax, y\rangle - g^*(y)

, where

f

is a convex function with locally Lipschitz gradient and

g

is convex and possibly non-smooth. We propose an ...

2021

Federated Learning Over Wireless Networks: Convergence Analysis and Resource Allocation

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Augmented Lagrangian Methods for Provable and Scalable Machine Learning

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A first-order primal-dual method with adaptivity to local smoothness

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Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Reinforcement Learning for Joint Design and Control of Battery-PV Systems

Feedback and Common Information: Bounds and Capacity for Gaussian Networks

Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization

Critical Parameters for Scalable Distributed Learning with Large Batches and Asynchronous Updates

A Multi-Agent Primal-Dual Strategy for Composite Optimization over Distributed Features

A first-order primal-dual method with adaptivity to local smoothness

SCAFFOLD Stochastic Controlled Averaging for Federated Learning

Scalable Convex Optimization Methods for Semidefinite Programming

Learning with Structured Sparsity: From Discrete to Convex and Back.