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Allaire, N., Le Digabel, S., Orban, D., & Partovi Nia, V. (2026). Zeroth-Order Kronecker Optimization for Pretraining Language Models. SN Computer Science, 7(2). Lien externe
Diouane, Y., Gollier, M., & Orban, D. (2026). Nonsmooth exact penalty methods for equality-constrained optimization: complexity and implementation. SIAM Journal on Optimization, 36(2), 626-650. Disponible
Diouane, Y., Habiboullah, M. L., & Orban, D. (2026). Complexity of trust-region methods in the presence of unbounded Hessian approximations. Mathematical Programming, 41 pages. Accès restreint
Diouane, Y., Habiboullah, M. L., & Orban, D. (2026). A proximal modified quasi-newton method for nonsmooth regularized optimization. SIAM Journal on Optimization, 36(2), 534-563. Disponible
Gollier, M., Habiboullah, M. L., Leconte, G., Baraldi, R., Marchi, A. D., Orban, D., & Diouane, Y. (2026). RegularizedOptimization.jl: A Julia framework for regularized and nonsmooth optimization. Journal of Open Source Software, 11(118), 9344 (4 pages). Disponible
Leconte, G., & Orban, D. (2026). Complexity of trust-region methods with potentially unbounded Hessian approximations for smooth and nonsmooth optimization. Mathematical Programming, 34 pages. Lien externe
Lotfi, S., Bonniot De Ruisselet, T. É., Orban, D., & Lodi, A. (2026). Adaptive First- and Second-Order Algorithms for Large-Scale Machine Learning. Dans Dang, S., Deza, A., Gupta, S., McNicholas, P. D., Pokutta, S., & Sugiyama, M. (édit.), Data Science and Optimization (Vol. 91, p. 273-302). Lien externe
