Laforgue, Pierre

13 publications

ECML-PKDD 2024 Deep Sketched Output Kernel Regression for Structured Prediction Tamim El Ahmad, Junjie Yang, Pierre Laforgue, Florence d'Alché-Buc

TMLR 2024 Linear Bandits with Memory Giulia Clerici, Pierre Laforgue, Nicolò Cesa-Bianchi

AISTATS 2024 Multitask Online Learning: Listen to the Neighborhood Buzz Juliette Achddou, Nicolò Cesa-Bianchi, Pierre Laforgue

AISTATS 2024 Sketch in, Sketch Out: Accelerating Both Learning and Inference for Structured Prediction with Kernels Tamim El Ahmad, Luc Brogat-Motte, Pierre Laforgue, Florence d’Alché-Buc

TMLR 2023 Fast Kernel Methods for Generic Lipschitz Losses via $p$-Sparsified Sketches Tamim El Ahmad, Pierre Laforgue, Florence d'Alché-Buc

NeurIPS 2023 Multitask Learning with No Regret: From Improved Confidence Bounds to Active Learning Pier Giuseppe Sessa, Pierre Laforgue, Nicolò Cesa-Bianchi, Andreas Krause

AISTATS 2022 A Last Switch Dependent Analysis of Satiation and Seasonality in Bandits Pierre Laforgue, Giulia Clerici, Nicolò Cesa-Bianchi, Ran Gilad-Bachrach

TMLR 2022 Multitask Online Mirror Descent Nicolò Cesa-Bianchi, Pierre Laforgue, Andrea Paudice, Massimiliano Pontil

AISTATS 2021 When OT Meets MoM: Robust Estimation of Wasserstein Distance Guillaume Staerman, Pierre Laforgue, Pavlo Mozharovskyi, Florence d’Alché-Buc

ICML 2021 Generalization Bounds in the Presence of Outliers: A Median-of-Means Study Pierre Laforgue, Guillaume Staerman, Stephan Clémençon

ICML 2020 Duality in RKHSs with Infinite Dimensional Outputs: Application to Robust Losses Pierre Laforgue, Alex Lambert, Luc Brogat-Motte, Florence D’Alché-Buc

AISTATS 2019 Autoencoding Any Data Through Kernel Autoencoders Pierre Laforgue, Stéphan Clémençon, Florence d’Alche-Buc

ICML 2019 On Medians of (Randomized) Pairwise Means Pierre Laforgue, Stephan Clemencon, Patrice Bertail