Guillaume Garrigos

19 papers A* 2A 2Journal 13Unranked 1
YearRankTypeTitle / Venue / Authors
2025 J jnl
Analysis of an Idealized Stochastic Polyak Method and its Application to Black-Box Model Distillation.
CoRR
Robert M. Gower, Guillaume Garrigos, Nicolas Loizou, Dimitris Oikonomou, Konstantin Mishchenko, Fabian Schaipp
2025 J jnl
New Tight Bounds for SGD without Variance Assumption: A Computer-Aided Lyapunov Analysis.
CoRR
Daniel Cortild, Lucas Ketels, Juan Peypouquet, Guillaume Garrigos
2025 J jnl
Tracking the Median of Gradients with a Stochastic Proximal Point Method.
Trans. Mach. Learn. Res.
Fabian Schaipp, Guillaume Garrigos, Umut Simsekli, Robert M. Gower
2024 J jnl
Multivariate Online Linear Regression for Hierarchical Forecasting.
CoRR
Massil Hihat, Guillaume Garrigos, Adeline Fermanian, Simon Bussy
2024 J jnl
SGD with Clipping is Secretly Estimating the Median Gradient.
CoRR
Fabian Schaipp, Guillaume Garrigos, Umut Simsekli, Robert M. Gower
2023 J jnl
Convergence of the forward-backward algorithm: beyond the worst-case with the help of geometry.
Math. Program.
Guillaume Garrigos, Lorenzo Rosasco, Silvia Villa
2023 J jnl
Function Value Learning: Adaptive Learning Rates Based on the Polyak Stepsize and Function Splitting in ERM.
CoRR
Guillaume Garrigos, Robert M. Gower, Fabian Schaipp
2023 A* conf
Online Inventory Problems: Beyond the i.i.d. Setting with Online Convex Optimization.
NeurIPS
Massil Hihat, Stéphane Gaïffas, Guillaume Garrigos, Simon Bussy
2023 J jnl
Online Inventory Problems: Beyond the i.i.d. Setting with Online Convex Optimization.
CoRR
Massil Hihat, Stéphane Gaïffas, Guillaume Garrigos, Simon Bussy
2023 A* conf
Provable convergence guarantees for black-box variational inference.
NeurIPS
Justin Domke, Robert M. Gower, Guillaume Garrigos
2023 J jnl
Provable convergence guarantees for black-box variational inference.
CoRR
Justin Domke, Guillaume Garrigos, Robert M. Gower
2022 A conf
SAN: Stochastic Average Newton Algorithm for Minimizing Finite Sums.
AISTATS
Jiabin Chen, Rui Yuan, Guillaume Garrigos, Robert M. Gower
2021 J jnl
Accelerated Iterative Regularization via Dual Diagonal Descent.
SIAM J. Optim.
Luca Calatroni, Guillaume Garrigos, Lorenzo Rosasco, Silvia Villa
2021 J jnl
SAN: Stochastic Average Newton Algorithm for Minimizing Finite Sums.
CoRR
Jiabin Chen, Rui Yuan, Guillaume Garrigos, Robert M. Gower
2019 A conf
Model Consistency for Learning with Mirror-Stratifiable Regularizers.
AISTATS
Jalal Fadili, Guillaume Garrigos, Jérôme Malick, Gabriel Peyré
2018 J jnl
Iterative Regularization via Dual Diagonal Descent.
J. Math. Imaging Vis.
Guillaume Garrigos, Lorenzo Rosasco, Silvia Villa
2018 — conf
Sparse Multiple Kernel Learning: Support Identification via Mirror Stratifiability.
EUSIPCO
Guillaume Garrigos, Lorenzo Rosasco, Silvia Villa
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 J jnl
Splitting Methods with Variable Metric for Kurdyka-Łojasiewicz Functions and General Convergence Rates.
J. Optim. Theory Appl.
Pierre Frankel, Guillaume Garrigos, Juan Peypouquet