Edouard Pauwels

Jérôme Bolte, Edouard Pauwels, and Quoc Tung Le, “Geometric and computational hardness of bilevel programming”, Mathematical Programming, vol. 215, January 2026, p. 539–574.

Jérôme Bolte, Tam Le, Eric Moulines, and Edouard Pauwels, “Inexact subgradient methods for semialgebraic functions”, Mathematical Programming, 2026, forthcoming.

Léo Portales, Elsa Cazelles, and Edouard Pauwels, “On the Sequential Convergence of Lloyd’s Algorithms”, Mathematics of Operations Research, 2025, forthcoming.

Jérôme Bolte, Cyrille Combettes, and Edouard Pauwels, “The Iterates of the Frank–Wolfe Algorithm May Not Converge”, Mathematics of Operations Research, vol. 49, n. 4, November 2024, pp. 2049–2802.

Edouard Pauwels, “On the nature of Bregman functions”, Operations Research Letters, vol. 57, n. 107183, November 2024.

Franck Iutzeler, Edouard Pauwels, and Samuel Vaiter, “Derivatives of Stochastic Gradient Descent in parametric optimization”, in Advances in Neural Information Processing Systems 37, A. Globerson, L. Mackey, D. Belgrave, A. Fan, U. Paquet, J. Tomczak, and Chi Zhang (eds.), 2024, pp. 118859–118882.

Jérôme Bolte, Edouard Pauwels, and Antonio Silveti-Falls, “Differentiating Nonsmooth Solutions to Parametric Monotone Inclusion Problems”, SIAM Journal on Optimization, vol. 34, n. 1, 2024, pp. 71–97.

Edouard Pauwels, “Conservative parametric optimality and the ridge method for tame min-max problems”, Set-Valued and Variational Analysis, vol. 31, n. 3, June 2023, p. 19.

Jérôme Bolte, Edouard Pauwels, and Samuel Vaiter, “Automatic differentiation of nonsmooth iterative algorithms”, in Advances in Neural Information Processing Systems 35, A. Oh, S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, and K. Cho (eds.), 2023, pp. 77089–77103.

Jérôme Bolte, Edouard Pauwels, and Samuel Vaiter, “One-step differentiation of iterative algorithms”, in Advances in Neural Information Processing Systems 36, A. Oh, T. Naumann, A. Globerson, K. Saenko, M. Hardt, and Sydney Levine (eds.), 2023, pp. 77089–77103.

Jérôme Bolte, Lilian Glaudin, Edouard Pauwels, and Matthieu Serrurier, “The backtrack Hölder gradient method with application to min-max and min-min problems”, Open Journal of Mathematical Optimization, vol. 4, n. 8, 2023, 17 pages.

M. Fabian, Jean-Baptiste Hiriart-Urruty, and Edouard Pauwels, “On the Generalized Jacobian of the Inverse of a Lipschitzian Mapping”, Set-Valued and Variational Analysis, vol. 30, May 2022, p. 1443–1451.

Tong Chen, Jean-Bernard Lasserre, Victor Magron, and Edouard Pauwels, “A sublevel moment-SOS hierarchy for polynomial optimization”, Computational Optimization and Applications, vol. 81, January 2022, pp. 31–66.

Jérôme Bolte, David Bertoin, Sebastien Gerchinovitz, and Edouard Pauwels, “Numerical influence of ReLU’(0) on backpropagation”, in Advances in Neural Information Processing Systems 34, M. Ranzato, A. Beygelzimer, Y. Dauphin, P.S. Liang, and J. Wortman Vaughan (eds.), 2021, pp. 468–479.

Jérôme Bolte, Tam Le, Edouard Pauwels, and Antonio Silveti-Falls, “Nonsmooth Implicit Differentiation for Machine Learning and Optimization”, in Advances in Neural Information Processing Systems 34, M. Ranzato, A. Beygelzimer, Y. Dauphin, P.S. Liang, and J. Wortman Vaughan (eds.), 2021, pp. 13537–13549.

Jérôme Bolte, Zheng Chen, and Edouard Pauwels, “The multiproximal linearization method for convex composite problems”, Mathematical Programming, vol. 182, July 2020, pp. 1–36.

Jérôme Bolte, and Edouard Pauwels, “Conservative set valued fields, automatic differentiation, stochastic gradient methods and deep learning”, Mathematical Programming, April 2020, pp. 1–33.

Jérôme Bolte, and Edouard Pauwels, “A mathematical model for automatic differentiation in machine learning”, in Advances in Neural Information Processing Systems, Hugo Larochelle, M. Ranzato, R. Hadsell, M.F. Balcan, and H. Lin (eds.), vol. 33, 2020.

Jérôme Bolte, Antoine Hochart, and Edouard Pauwels, “Qualification conditions in semi-algebraic programming”, SIAM Journal on Optimization, vol. 28, n. 2, 2018, pp. 1867–1891.

Jérôme Bolte, and Edouard Pauwels, “Majorization-minimization procedures and convergence of SQP methods for semi-algebraic and tame programs”, Mathematics of Operations Research, January 2016, pp. 442–465.