Yassine Laguel

16 papers A* 1Misc 1Journal 12Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Fairness-informed Pareto Optimization : An Efficient Bilevel Framework.
CoRR
Sofiane Tanji, Samuel Vaiter, Yassine Laguel
2024 J jnl
Chance-constrained programs with convex underlying functions: a bilevel convex optimization perspective.
Comput. Optim. Appl.
Yassine Laguel, Jérôme Malick, Wim van Ackooij
2024 J jnl
Federated learning with superquantile aggregation for heterogeneous data.
Mach. Learn.
Krishna Pillutla, Yassine Laguel, Jérôme Malick, Zaïd Harchaoui
2024 J jnl
High Probability and Risk-Averse Guarantees for a Stochastic Accelerated Primal-Dual Method.
J. Mach. Learn. Res.
Yassine Laguel, Necdet Serhat Aybat, Mert Gürbüzbalaban
2024 A* conf
High-probability complexity bounds for stochastic non-convex minimax optimization.
NeurIPS
Yassine Laguel, Yasa Syed, Necdet Serhat Aybat, Mert Gürbüzbalaban
2023 J jnl
Push-Pull With Device Sampling.
IEEE Trans. Autom. Control.
Yu-Guan Hsieh, Yassine Laguel, Franck Iutzeler, Jérôme Malick
2022 J jnl
Push-Pull with Device Sampling.
CoRR
Yu-Guan Hsieh, Yassine Laguel, Franck Iutzeler, Jérôme Malick
2022 J jnl
Superquantile-Based Learning: A Direct Approach Using Gradient-Based Optimization.
J. Signal Process. Syst.
Yassine Laguel, Jérôme Malick, Zaïd Harchaoui
2021 Misc conf
A Superquantile Approach to Federated Learning with Heterogeneous Devices.
CISS
Yassine Laguel, Krishna Pillutla, Jérôme Malick, Zaïd Harchaoui
2021 — —
Convex optimization for risk-sensitive learning. (Optimisation convexe pour l'apprentissage robuste au risque).
Yassine Laguel
2021 J jnl
Federated Learning with Heterogeneous Data: A Superquantile Optimization Approach.
CoRR
Krishna Pillutla, Yassine Laguel, Jérôme Malick, Zaïd Harchaoui
2020 J jnl
Device Heterogeneity in Federated Learning: A Superquantile Approach.
CoRR
Yassine Laguel, Krishna Pillutla, Jérôme Malick, Zaïd Harchaoui
2020 — conf
First-Order Optimization for Superquantile-Based Supervised Learning.
MLSP
Yassine Laguel, Jérôme Malick, Zaïd Harchaoui
2020 J jnl
First-order Optimization for Superquantile-based Supervised Learning.
CoRR
Yassine Laguel, Jérôme Malick, Zaïd Harchaoui
2020 J jnl
Randomized Progressive Hedging methods for Multi-stage Stochastic Programming.
CoRR
Gilles Bareilles, Yassine Laguel, Dmitry Grishchenko, Franck Iutzeler, Jérôme Malick
2020 J jnl
Randomized Progressive Hedging methods for multi-stage stochastic programming.
Ann. Oper. Res.
Gilles Bareilles, Yassine Laguel, Dmitry Grishchenko, Franck Iutzeler, Jérôme Malick