Publications associées à Composite Self-Concordant Minimization

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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

Composite Self-Concordant Minimization

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Social Learning with Disparate Hypotheses

An Accelerated First-Order Method for Non-convex Optimization on Manifolds

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

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

A Newton Frank-Wolfe method for constrained self-concordant minimization

Data-Driven Chance Constrained Programs over Wasserstein Balls

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

Composite convex minimization involving self-concordant-like cost functions

Composite convex minimization involving self-concordant-like cost functions

Path-following gradient-based decomposition algorithms for separable convex optimization

An Accelerated First-Order Method for Non-convex Optimization on Manifolds

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

Data-Driven Chance Constrained Programs over Wasserstein Balls

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

Social Learning with Disparate Hypotheses

Path-following gradient-based decomposition algorithms for separable convex optimization

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

Composite convex minimization involving self-concordant-like cost functions

Composite convex minimization involving self-concordant-like cost functions

A Newton Frank-Wolfe method for constrained self-concordant minimization