Pierre Laforgue

According to our database, Pierre Laforgue authored at least 21 papers between 1975 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Linear Bandits with Memory.

Giulia Clerici, Pierre Laforgue, Nicolò Cesa-Bianchi

Trans. Mach. Learn. Res., 2024

Deep Sketched Output Kernel Regression for Structured Prediction.

Tamim El Ahmad, Junjie Yang, Pierre Laforgue, Florence d'Alché-Buc

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 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

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Multitask Online Learning: Listen to the Neighborhood Buzz.

Juliette Achddou, Nicolò Cesa-Bianchi, Pierre Laforgue

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Fast Kernel Methods for Generic Lipschitz Losses via p-Sparsified Sketches.

Tamim El Ahmad, Pierre Laforgue, Florence d'Alché-Buc

Trans. Mach. Learn. Res., 2023

Linear Bandits with Memory: from Rotting to Rising.

Giulia Clerici, Pierre Laforgue, Nicolò Cesa-Bianchi

CoRR, 2023

Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning.

Pier Giuseppe Sessa, Pierre Laforgue, Nicolò Cesa-Bianchi, Andreas Krause

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Multitask Online Mirror Descent.

Nicolò Cesa-Bianchi, Pierre Laforgue, Andrea Paudice, Massimiliano Pontil

Trans. Mach. Learn. Res., 2022

p-Sparsified Sketches for Fast Multiple Output Kernel Methods.

Tamim El Ahmad, Pierre Laforgue, Florence d'Alché-Buc

CoRR, 2022

A Last Switch Dependent Analysis of Satiation and Seasonality in Bandits.

Pierre Laforgue, Giulia Clerici, Nicolò Cesa-Bianchi, Ran Gilad-Bachrach

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Break your Bandit Routine with LSD Rewards: a Last Switch Dependent Analysis of Satiation and Seasonality.

Pierre Laforgue, Giulia Clerici, Nicolò Cesa-Bianchi, Ran Gilad-Bachrach

CoRR, 2021

Visual Recognition with Deep Learning from Biased Image Datasets.

Robin Vogel, Stéphan Clémençon, Pierre Laforgue

CoRR, 2021

Generalization Bounds in the Presence of Outliers: a Median-of-Means Study.

Pierre Laforgue, Guillaume Staerman, Stéphan Clémençon

Proceedings of the 38th International Conference on Machine Learning, 2021

When OT meets MoM: Robust estimation of Wasserstein Distance.

Guillaume Staerman, Pierre Laforgue, Pavlo Mozharovskyi, Florence d'Alché-Buc

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

How Robust is the Median-of-Means? Concentration Bounds in Presence of Outliers.

Pierre Laforgue, Guillaume Staerman, Stéphan Clémençon

CoRR, 2020

Duality in RKHSs with Infinite Dimensional Outputs: Application to Robust Losses.

Pierre Laforgue, Alex Lambert, Luc Brogat-Motte, Florence d'Alché-Buc

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

On the Dualization of Operator-Valued Kernel Machines.

Pierre Laforgue, Alex Lambert, Luc Motte, Florence d'Alché-Buc

CoRR, 2019

Statistical Learning from Biased Training Samples.

Pierre Laforgue, Stéphan Clémençon

CoRR, 2019

On Medians of (Randomized) Pairwise Means.

Stéphan Clémençon, Pierre Laforgue, Patrice Bertail

Proceedings of the 36th International Conference on Machine Learning, 2019

Autoencoding any Data through Kernel Autoencoders.

Pierre Laforgue, Stéphan Clémençon, Florence d'Alché-Buc

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

1975

Construction de sous-systèmes utilisant une machine abstraite. Réalisation autour du noyau GEMAU.

Pierre Laforgue

PhD thesis, 1975