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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

Ensemble convexe

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

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

Extra Newton: A First Approach to Noise-Adaptive Accelerated Second-Order Methods

Sharp asymptotics on the compression of two-layer neural networks

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

Reactive Navigation in Crowds for Non-holonomic Robots with Convex Bounding Shape

Invariant integrals on topological groups

Learning of Continuous and Piecewise-Linear Functions With Hessian Total-Variation Regularization

A convex set of robust D—stabilizing controllers using Cauchy's argument principle

Flow Time Scheduling and Prefix Beck-Fiala

Finding stationary points on bounded-rank matrices: a geometric hurdle and a smooth remedy