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Yakov Vaisbourd
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2020 – today
- 2023
- [j6]Marc Teboulle
, Yakov Vaisbourd:
An elementary approach to tight worst case complexity analysis of gradient based methods. Math. Program. 201(1): 63-96 (2023) - 2022
- [i2]Yakov Vaisbourd, Rustum Choksi, Ariel Goodwin, Tim Hoheisel, Carola-Bibiane Schönlieb:
Maximum Entropy on the Mean and the Cramér Rate Function in Statistical Estimation and Inverse Problems: Properties, Models, and Algorithms. CoRR abs/2211.05205 (2022) - 2020
- [j5]Marc Teboulle
Novel Proximal Gradient Methods for Nonnegative Matrix Factorization with Sparsity Constraints. SIAM J. Imaging Sci. 13(1): 381-421 (2020)
2010 – 2019
- 2018
- [j4]Amir Beck, Yakov Vaisbourd:
Globally Solving the Trust Region Subproblem Using Simple First-Order Methods. SIAM J. Optim. 28(3): 1951-1967 (2018) - [j3]Jérôme Bolte, Shoham Sabach, Marc Teboulle
First Order Methods Beyond Convexity and Lipschitz Gradient Continuity with Applications to Quadratic Inverse Problems. SIAM J. Optim. 28(3): 2131-2151 (2018) - 2017
- [i1]Jérôme Bolte, Shoham Sabach, Marc Teboulle, Yakov Vaisbourd:
First Order Methods beyond Convexity and Lipschitz Gradient Continuity with Applications to Quadratic Inverse Problems. CoRR abs/1706.06461 (2017) - 2016
- [j2]Amir Beck, Yakov Vaisbourd:
The Sparse Principal Component Analysis Problem: Optimality Conditions and Algorithms. J. Optim. Theory Appl. 170(1): 119-143 (2016) - [j1]Amir Beck, Luba Tetruashvili, Yakov Vaisbourd, Ariel Shemtov:
Rate of convergence analysis of dual-based variables decomposition methods for strongly convex problems. Oper. Res. Lett. 44(1): 61-66 (2016)
Coauthor Index
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