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Stochastic first-order algorithms for constrained distributionally robust optimization

Im, Hyungki; Grigas, Paul - In: INFORMS journal on computing : JOC ; charting new … 37 (2025) 2, pp. 212-229

Persistent link: https://www.econbiz.de/10015434231

First-order algorithms for robust optimization problems via convex-concave saddle-point Lagrangian reformulation

Postek, Krzysztof; Shtern, Shimrit - In: INFORMS journal on computing : JOC ; charting new … 37 (2025) 3, pp. 557-581

Persistent link: https://www.econbiz.de/10015434710

Frank-Wolfe and friends : a journey into projection-free first-order optimization methods

Bomze, Immanuel M.; Rinaldi, Francesco; Zeffiro, Damiano - In: 4OR : quarterly journal of the Belgian, French and … 19 (2021) 3, pp. 313-345

Persistent link: https://www.econbiz.de/10012650681

Coordinate descent without coordinates : tangent subspace descent on riemannian manifolds

Gutman, David Huckleberry; Ho-Nguyen, Nam - In: Mathematics of operations research 48 (2023) 1, pp. 127-159

Persistent link: https://www.econbiz.de/10014312537

Iteration complexity of a proximal augmented lagrangian method for solving nonconvex composite optimization problems with nonlinear convex constraints

Kong, Weiwei; Melo, Jefferson G.; Monteiro, Renato D. C. - In: Mathematics of operations research 48 (2023) 2, pp. 1066-1094

Persistent link: https://www.econbiz.de/10014314979

On the efficient implementation of the matrix exponentiated gradient algorithm for low-rank matrix optimization

Garber, Dan; Kaplan, Atara - In: Mathematics of operations research 48 (2023) 4, pp. 2094-2128

Persistent link: https://www.econbiz.de/10014437817

Accelerated methods for weakly-quasi-convex optimization problems

Guminov, Sergey; Gasnikov, Alexander; Kuruzov, Ilya - In: Computational management science 20 (2023) 1, pp. 1-19

Persistent link: https://www.econbiz.de/10014393397

Preconditioning meets biased compression for efficient distributed optimization

Pirau, Vitali; Beznosikov, Aleksandr; Takáč, Martin; … - In: Computational management science 21 (2023) 1, pp. 1-22

Persistent link: https://www.econbiz.de/10014636773

On the convergence rate of the Halpern-iteration

Lieder, Felix - In: Optimization Letters 15 (2020) 2, pp. 405-418

In this work, we give a tight estimate of the rate of convergence for the Halpern-iteration for approximating a fixed point of a nonexpansive mapping in a Hilbert space. Specifically, using semidefinite programming and duality we prove that the norm of the residuals is upper bounded by the...

Persistent link: https://www.econbiz.de/10014504510

Conservative set valued fields, automatic differentiation, stochastic gradient methods and deep learning

Bolte, Jérôme; Pauwels, Edouard - 2019

Persistent link: https://www.econbiz.de/10012182324

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