A Dynamic Sampling Adaptive-SGD Method for Machine Learning. - Achraf Bahamou; Donald Goldfarb (CoRR, 2019)

Stochastic Flows and Geometric Optimization on the Orthogonal Group. - Krzysztof Choromanski; David Cheikhi; Jared Davis; Valerii Likhosherstov; Achille Nazaret; Achraf Bahamou; Xingyou Song; Mrugank Akarte; Jack Parker-Holder; Jacob Bergquist; Yuan Gao 038; Aldo Pacchiano; et al. (ICML, 2020)

Practical Quasi-Newton Methods for Training Deep Neural Networks. - Donald Goldfarb; Yi Ren 007; Achraf Bahamou (NeurIPS, 2020)

Optimal Pricing with a Single Point. - Amine Allouah; Achraf Bahamou; Omar Besbes (EC, 2021)

Revenue Maximization from Finite Samples. - Amine Allouah; Achraf Bahamou; Omar Besbes (EC, 2021)

A Mini-Block Natural Gradient Method for Deep Neural Networks. - Achraf Bahamou; Donald Goldfarb; Yi Ren 007 (CoRR, 2022)

Pricing with Samples. - Amine Allouah; Achraf Bahamou; Omar Besbes (Oper. Res., 2022)

A Mini-Block Fisher Method for Deep Neural Networks. - Achraf Bahamou; Donald Goldfarb; Yi Ren 007 (AISTATS, 2023)

Topics in Deep Learning and Data-driven Optimization - Achraf Bahamou (2023)

Fast Revenue Maximization. - Achraf Bahamou; Omar Besbes; Omar Mouchtaki (CoRR, 2024)