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Optimization with Sparsity-Inducing Penalties

Foundations and trends in machine learning, 2012, Vol.4 (1), p.1-106

Bach, Francis

2012

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Minimizing finite sums with the stochastic average gradient

Mathematical programming, 2017-03, Vol.162 (1-2), p.83-112

2017

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Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward–backward splitting, and regularized Gauss–Seidel methods

Mathematical programming, 2013-02, Vol.137 (1-2), p.91-129

2013

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First-order optimization algorithms via inertial systems with Hessian driven damping

Mathematical programming, 2022-05, Vol.193 (1), p.113-155

2022

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Fast convergence of inertial dynamics and algorithms with asymptotic vanishing viscosity

Mathematical programming, 2018-03, Vol.168 (1-2), p.123-175

2018

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Proximal alternating linearized minimization for nonconvex and nonsmooth problems

Mathematical programming, 2014-08, Vol.146 (1-2), p.459-494

2014

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Phase recovery, MaxCut and complex semidefinite programming

Mathematical programming, 2015-02, Vol.149 (1-2), p.47-81

2015

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A Primal–Dual Splitting Method for Convex Optimization Involving Lipschitzian, Proximable and Linear Composite Terms

Journal of optimization theory and applications, 2013-08, Vol.158 (2), p.460-479

Condat, Laurent

2013

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Convergence analysis of a Lasserre hierarchy of upper bounds for polynomial minimization on the sphere

Mathematical programming, 2022-06, Vol.193 (2), p.665-685

2022

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The Pontryagin Maximum Principle in the Wasserstein Space

Calculus of variations and partial differential equations, 2019-02, Vol.58 (1), p.1-36, Article 11

2019

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A Newton-CG algorithm with complexity guarantees for smooth unconstrained optimization

Mathematical programming, 2020-03, Vol.180 (1-2), p.451-488

2020

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Optimal complexity and certification of Bregman first-order methods

Mathematical programming, 2022-07, Vol.194 (1-2), p.41-83

2022

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Convergence rate of inertial Forward–Backward algorithm beyond Nesterov’s rule

Mathematical programming, 2020-03, Vol.180 (1-2), p.137-156

2020

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Mean field games with state constraints: from mild to pointwise solutions of the PDE system

Calculus of variations and partial differential equations, 2021-06, Vol.60 (3), p.1-33, Article 108

2021

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Convergence of the forward-backward algorithm: beyond the worst-case with the help of geometry

Mathematical programming, 2023-03, Vol.198 (1), p.937-996

2023

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Necessary Optimality Conditions for Optimal Control Problems in Wasserstein Spaces

Applied mathematics & optimization, 2021-12, Vol.84 (Suppl 2), p.1281-1330

2021

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Superfast Second-Order Methods for Unconstrained Convex Optimization

Journal of optimization theory and applications, 2021-10, Vol.191 (1), p.1-30

Nesterov, Yurii

2021

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Conditional gradient algorithms for norm-regularized smooth convex optimization

Mathematical programming, 2015-08, Vol.152 (1-2), p.75-112

2015

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Prophet secretary through blind strategies

Mathematical programming, 2021-11, Vol.190 (1-2), p.483-521

2021

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Efficient first-order methods for convex minimization: a constructive approach

Mathematical programming, 2020-11, Vol.184 (1-2), p.183-220

2020

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Split Monotone Variational Inclusions

Journal of optimization theory and applications, 2011-08, Vol.150 (2), p.275-283

Moudafi, A.

2011

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Regularized nonlinear acceleration

Mathematical programming, 2020-01, Vol.179 (1-2), p.47-83

2020

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Mean-Field Pontryagin Maximum Principle

Journal of optimization theory and applications, 2017-10, Vol.175 (1), p.1-38

2017

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Convergence of inertial dynamics and proximal algorithms governed by maximally monotone operators

Mathematical programming, 2019-03, Vol.174 (1-2), p.391-432

2019

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Linfty/L1 duality results in optimal control problems

IEEE transactions on automatic control, 2024-04

2024

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Optimization with Sparsity-Inducing Penalties

Minimizing finite sums with the stochastic average gradient

Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward–backward splitting, and regularized Gauss–Seidel methods

First-order optimization algorithms via inertial systems with Hessian driven damping

Fast convergence of inertial dynamics and algorithms with asymptotic vanishing viscosity

Proximal alternating linearized minimization for nonconvex and nonsmooth problems

Phase recovery, MaxCut and complex semidefinite programming

A Primal–Dual Splitting Method for Convex Optimization Involving Lipschitzian, Proximable and Linear Composite Terms

Convergence analysis of a Lasserre hierarchy of upper bounds for polynomial minimization on the sphere

The Pontryagin Maximum Principle in the Wasserstein Space

A Newton-CG algorithm with complexity guarantees for smooth unconstrained optimization

Optimal complexity and certification of Bregman first-order methods

Convergence rate of inertial Forward–Backward algorithm beyond Nesterov’s rule

Mean field games with state constraints: from mild to pointwise solutions of the PDE system

Convergence of the forward-backward algorithm: beyond the worst-case with the help of geometry

Necessary Optimality Conditions for Optimal Control Problems in Wasserstein Spaces

Superfast Second-Order Methods for Unconstrained Convex Optimization

Conditional gradient algorithms for norm-regularized smooth convex optimization

Prophet secretary through blind strategies

Efficient first-order methods for convex minimization: a constructive approach

Split Monotone Variational Inclusions

Regularized nonlinear acceleration

Mean-Field Pontryagin Maximum Principle

Convergence of inertial dynamics and proximal algorithms governed by maximally monotone operators

Linfty/L1 duality results in optimal control problems

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