Mathias Staudigl | DeepAI

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Paulin Jacquot
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Barbara Franci
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∙ 02/13/2023

A regularized variance-reduced modified extragradient method for stochastic hierarchical games

The theory of learning in games has so far focused mainly on games with ...

0 Shisheng Cui, et al. ∙

∙ 12/22/2022

Distributed Random Block-Coordinate descent methods for ill-posed composite convex optimisation problems

We develop a novel randomised block coordinate descent primal-dual algor...

0 Mathias Staudigl, et al. ∙

∙ 07/07/2022

A conditional gradient homotopy method with applications to Semidefinite Programming

We propose a new homotopy-based conditional gradient method for solving ...

0 Pavel Dvurechensky, et al. ∙

∙ 03/29/2022

Proximal-like algorithms for equilibrium seeking in mixed-integer Nash equilibrium problems

We consider potential games with mixed-integer variables, for which we p...

0 Filippo Fabiani, et al. ∙

∙ 03/08/2022

Mini-batch stochastic three-operator splitting for distributed optimization

We consider a network of agents, each with its own private cost consisti...

0 Barbara Franci, et al. ∙

∙ 03/24/2021

A relaxed-inertial forward-backward-forward algorithm for Stochastic Generalized Nash equilibrium seeking

In this paper we propose a new operator splitting algorithm for distribu...

0 Shisheng Cui, et al. ∙

∙ 01/04/2021

First-Order Methods for Convex Optimization

First-order methods for solving convex optimization problems have been a...

0 Pavel Dvurechensky, et al. ∙

∙ 08/27/2020

A competitive search game with a moving target

We introduce a discrete-time search game, in which two players compete t...

0 Benoit Duvocelle, et al. ∙

∙ 04/04/2020

Incentive compatibility in sender-receiver stopping games

We introduce a model of sender-receiver stopping games, where the state ...

0 Aditya Aradhye, et al. ∙

∙ 02/11/2020

Self-concordant analysis of Frank-Wolfe algorithms

Projection-free optimization via different variants of the Frank-Wolfe (...

0 Pavel Dvurechensky, et al. ∙

∙ 11/12/2019

Inducing strong convergence of trajectories in dynamical systems associated to monotone inclusions with composite structure

In this work we investigate dynamical systems designed to approach the s...

0 Radu Ioan Bot, et al. ∙

∙ 11/04/2019

Generalized Self-concordant Hessian-barrier algorithms

Many problems in statistical learning, imaging, and computer vision invo...

0 Pavel Dvurechensky, et al. ∙

∙ 10/30/2019

Distributed forward-backward (half) forward algorithms for generalized Nash equilibrium seeking

We present two distributed algorithms for the computation of a generaliz...

0 Barbara Franci, et al. ∙

∙ 02/09/2019

Forward-backward-forward methods with variance reduction for stochastic variational inequalities

We develop a new stochastic algorithm with variance reduction for solvin...

0 Radu Ioan Bot, et al. ∙

∙ 09/25/2018

Hessian barrier algorithms for linearly constrained optimization problems

In this paper, we propose an interior-point method for linearly constrai...

0 Immanuel M. Bomze, et al. ∙

∙ 09/10/2018

Learning in time-varying games

In this paper, we examine the long-term behavior of regret-minimizing ag...

0 Benoit Duvocelle, et al. ∙

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