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First-Order Methods for Convex Optimization

  • Published:2021 Issue: Volume:9 Page:100015
  • ISSN:2192-4406
  • Container-title:EURO Journal on Computational Optimization
  • language:en
  • Short-container-title:EURO Journal on Computational Optimization

Author:

Dvurechensky Pavel,Shtern ShimritORCID,Staudigl MathiasORCID

Funder

Ministry of Education and Science of the Russian Federation

Fondation Mathematiques Jacques Hadamard

EDF Energy

European Cooperation in Science and Technology

Publisher

Elsevier BV

Subject

Computational Mathematics,Control and Optimization,Management Science and Operations Research,Modeling and Simulation

Reference238 articles.

1. Smooth primal-dual coordinate descent algorithms for nonsmooth convex optimization;Alacaoglu,2017

2. Katyusha: The first direct acceleration of stochastic gradient methods;Allen-Zhu,2017

3. Optimal black-box reductions between optimization objectives;Allen-Zhu,2016

4. Hessian Riemannian gradient flows in convex programming;Alvarez;SIAM Journal on Control and Optimization,2004

5. The Mosek Interior Point Optimizer for Linear Programming: An Implementation of the Homogeneous Algorithm;Andersen,2000

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