Splitting Methods with Variable Metric for Kurdyka-Łojasiewicz Functions and General Convergence Rates. - Pierre Frankel; Guillaume Garrigos; Juan Peypouquet (J. Optim. Theory Appl., 2015)

Descent dynamical systems and algorithms for tame optimization, and multi-objective problems. (Systèmes dynamiques de descente et algorithmes pour l'optimisation modérée, et les problèmes multi-objectif). - Guillaume Garrigos (2015)

Sparse Multiple Kernel Learning: Support Identification via Mirror Stratifiability. - Guillaume Garrigos; Lorenzo Rosasco; Silvia Villa (EUSIPCO, 2018)

Iterative Regularization via Dual Diagonal Descent. - Guillaume Garrigos; Lorenzo Rosasco; Silvia Villa (J. Math. Imaging Vis., 2018)

Model Consistency for Learning with Mirror-Stratifiable Regularizers. - Jalal Fadili; Guillaume Garrigos; Jérôme Malick; Gabriel Peyré (AISTATS, 2019)

Accelerated Iterative Regularization via Dual Diagonal Descent. - Luca Calatroni; Guillaume Garrigos; Lorenzo Rosasco; Silvia Villa (SIAM J. Optim., 2021)

SAN: Stochastic Average Newton Algorithm for Minimizing Finite Sums. - Jiabin Chen; Rui Yuan; Guillaume Garrigos; Robert M. Gower (AISTATS, 2022)

Provable convergence guarantees for black-box variational inference. - Justin Domke; Robert M. Gower; Guillaume Garrigos (NeurIPS, 2023)

Online Inventory Problems: Beyond the i.i.d. Setting with Online Convex Optimization. - Massil Hihat; Stéphane Gaïffas; Guillaume Garrigos; Simon Bussy (NeurIPS, 2023)

Function Value Learning: Adaptive Learning Rates Based on the Polyak Stepsize and Function Splitting in ERM. - Guillaume Garrigos; Robert M. Gower; Fabian Schaipp (CoRR, 2023)

Convergence of the forward-backward algorithm: beyond the worst-case with the help of geometry. - Guillaume Garrigos; Lorenzo Rosasco; Silvia Villa (Math. Program., 2023)

SGD with Clipping is Secretly Estimating the Median Gradient. - Fabian Schaipp; Guillaume Garrigos; Umut Simsekli; Robert M. Gower (CoRR, 2024)

Multivariate Online Linear Regression for Hierarchical Forecasting. - Massil Hihat; Guillaume Garrigos; Adeline Fermanian; Simon Bussy (CoRR, 2024)

Analysis of an Idealized Stochastic Polyak Method and its Application to Black-Box Model Distillation. - Robert M. Gower; Guillaume Garrigos; Nicolas Loizou; Dimitris Oikonomou; Konstantin Mishchenko; Fabian Schaipp (CoRR, 2025)

New Tight Bounds for SGD without Variance Assumption: A Computer-Aided Lyapunov Analysis. - Daniel Cortild; Lucas Ketels; Juan Peypouquet; Guillaume Garrigos (CoRR, 2025)