Publications associées à Convex Combination of Diffusion Strategies Over Networks

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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

Convex Combination of Diffusion Strategies Over Networks

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Fast parametric analysis of trimmed multi-patch isogeometric Kirchhoff-Love shells using a local reduced basis method

Stochastic homogenization of degenerate integral functionals with linear growth

Stochastic distributed learning with gradient quantization and double-variance reduction

Flow Time Scheduling and Prefix Beck-Fiala

Singularities of general fibers and the LMMP

On the Equivalence of Youla, System-Level, and Input-Output Parameterizations

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

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

Adaptation in Stochastic Algorithms: From Nonsmooth Optimization to Min-Max Problems and Beyond

Deep Boltzmann Machines: Rigorous Results at Arbitrary Depth

Flow Time Scheduling and Prefix Beck-Fiala

Fast parametric analysis of trimmed multi-patch isogeometric Kirchhoff-Love shells using a local reduced basis method

Stochastic distributed learning with gradient quantization and double-variance reduction

Singularities of general fibers and the LMMP

On the Equivalence of Youla, System-Level, and Input-Output Parameterizations

Deep Boltzmann Machines: Rigorous Results at Arbitrary Depth

Adaptation in Stochastic Algorithms: From Nonsmooth Optimization to Min-Max Problems and Beyond

Stochastic homogenization of degenerate integral functionals with linear growth

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

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