Towards closing the gap between the theory and practice of SVRG. - Othmane Sebbouh; Nidham Gazagnadou; Samy Jelassi; Francis R. Bach; Robert M. Gower (NeurIPS, 2019)

On the convergence of the Stochastic Heavy Ball Method. - Othmane Sebbouh; Robert M. Gower; Aaron Defazio (CoRR, 2020)

Convergence Rates of Damped Inertial Dynamics under Geometric Conditions and Perturbations. - Othmane Sebbouh; Charles Dossal; Aude Rondepierre (SIAM J. Optim., 2020)

SGD for Structured Nonconvex Functions: Learning Rates, Minibatching and Interpolation. - Robert M. Gower; Othmane Sebbouh; Nicolas Loizou (AISTATS, 2021)

Almost sure convergence rates for Stochastic Gradient Descent and Stochastic Heavy Ball. - Othmane Sebbouh; Robert M. Gower; Aaron Defazio (COLT, 2021)

Randomized Stochastic Gradient Descent Ascent. - Othmane Sebbouh; Marco Cuturi; Gabriel Peyré (AISTATS, 2022)

Unified Analysis of Stochastic Gradient Methods for Composite Convex and Smooth Optimization. - Ahmed Khaled 001; Othmane Sebbouh; Nicolas Loizou; Robert M. Gower; Peter Richtárik (J. Optim. Theory Appl., 2023)

Structured Transforms Across Spaces with Cost-Regularized Optimal Transport. - Othmane Sebbouh; Marco Cuturi; Gabriel Peyré (AISTATS, 2024)