Publications associées à A Non-Euclidean Gradient Descent Framework for Non-Convex Matrix Factorization

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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

A Non-Euclidean Gradient Descent Framework for Non-Convex Matrix Factorization

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

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Scalable Semidefinite Programming

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

Universal and adaptive methods for robust stochastic optimization

Safe Zeroth-Order Convex Optimization Using Quadratic Local Approximations

Adaptive Gradient Descent without Descent

Implications of ANEC for SCFTs in four dimensions

Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization