Publications associées à On the convergence of stochastic primal-dual hybrid gradient

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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

On the convergence of stochastic primal-dual hybrid gradient

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Augmented Lagrangian Methods for Provable and Scalable Machine Learning

A Spatial Branch and Bound Algorithm for Continuous Pricing with Advanced Discrete Choice Demand Modeling

Localizing Unsynchronized Sensors With Unknown Sources

Stochastic homogenization of degenerate integral functionals with linear growth

On The Convergence Of Stochastic Primal-Dual Hybrid Gradient

Stochastic distributed learning with gradient quantization and double-variance reduction

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

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Augmented Lagrangian Methods for Provable and Scalable Machine Learning

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

A Spatial Branch and Bound Algorithm for Continuous Pricing with Advanced Discrete Choice Demand Modeling

Stochastic homogenization of degenerate integral functionals with linear growth

On The Convergence Of Stochastic Primal-Dual Hybrid Gradient

Stochastic distributed learning with gradient quantization and double-variance reduction

Localizing Unsynchronized Sensors With Unknown Sources

Integrating advanced discrete choice models in mixed integer linear optimization

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

Mathematical Foundations of Robust and Distributionally Robust Optimization