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Majorization-minimization procedures and convergence of SQP methods for semi-algebraic and tame programs
Bolte, Jérôme; Pauwels, Edouard - In: Mathematics of operations research 41 (2016) 2, pp. 442-465
Persistent link: https://www.econbiz.de/10011520454
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Nonsmooth implicit differentiation for machine learning and optimization
Bolte, Jérôme; Le, Tam; Pauwels, Edouard; … - 2022
Persistent link: https://www.econbiz.de/10013170004
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A Hölderian backtracking method for min-max and min-min problems
Bolte, Jérôme; Glaudin, Lilian; Pauwels, Edouard; … - 2021
Persistent link: https://www.econbiz.de/10012614580
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Subgradient sampling for nonsmooth nonconvex minimization
Bolte, Jérôme; Le, Tam; Pauwels, Edouard - 2022
Persistent link: https://www.econbiz.de/10012888151
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The iterates of the Frank-Wolfe algorithm may not converge
Bolte, Jérôme; Combettes, Cyrille W.; Pauwels, Edouard - 2022
Persistent link: https://www.econbiz.de/10012888152
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Sequential convergence of AdaGrad algorithm for smooth convex optimization
Traoré, Cheik; Pauwels, Edouard - In: Operations research letters 49 (2021) 4, pp. 452-458
Persistent link: https://www.econbiz.de/10012649005
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"Long term dynamics of the subgradient method for Lipschitz path differentiable functions"
Bolte, Jérôme; Pauwels, Edouard; Rios-Zertuche, Rodolfo - 2020
Persistent link: https://www.econbiz.de/10012264645
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An inertial Newton algorithm for deep learning
Bolte, Jérôme; Castera, Camille; Pauwels, Edouard; … - 2019
Persistent link: https://www.econbiz.de/10012182314
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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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Curiosities and counterexamples in smooth convex optimization
Bolte, Jérôme; Pauwels, Edouard - 2020 - Draft of January 21, 2020
Persistent link: https://www.econbiz.de/10012194774