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2020 – today
- 2024
[j3]Giulia Clerici, Pierre Laforgue, Nicolò Cesa-Bianchi:
Linear Bandits with Memory. Trans. Mach. Learn. Res. 2024 (2024)- [c10]Tamim El Ahmad, Luc Brogat-Motte, Pierre Laforgue, Florence d'Alché-Buc:
Sketch In, Sketch Out: Accelerating both Learning and Inference for Structured Prediction with Kernels. AISTATS 2024: 109-117 - [c9]Juliette Achddou, Nicolò Cesa-Bianchi, Pierre Laforgue:
Multitask Online Learning: Listen to the Neighborhood Buzz. AISTATS 2024: 1846-1854 - [c8]Tamim El Ahmad, Junjie Yang, Pierre Laforgue, Florence d'Alché-Buc:
Deep Sketched Output Kernel Regression for Structured Prediction. ECML/PKDD (3) 2024: 93-110 - [i15]Tamim El Ahmad, Junjie Yang, Pierre Laforgue, Florence d'Alché-Buc:
Deep Sketched Output Kernel Regression for Structured Prediction. CoRR abs/2406.09253 (2024) - 2023
- [j2]Tamim El Ahmad, Pierre Laforgue, Florence d'Alché-Buc:
Fast Kernel Methods for Generic Lipschitz Losses via p-Sparsified Sketches. Trans. Mach. Learn. Res. 2023 (2023) - [c7]Pier Giuseppe Sessa, Pierre Laforgue, Nicolò Cesa-Bianchi, Andreas Krause:
Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning. NeurIPS 2023 - [i14]Giulia Clerici, Pierre Laforgue, Nicolò Cesa-Bianchi:
Linear Bandits with Memory: from Rotting to Rising. CoRR abs/2302.08345 (2023) - [i13]Tamim El Ahmad, Luc Brogat-Motte, Pierre Laforgue, Florence d'Alché-Buc:
Sketch In, Sketch Out: Accelerating both Learning and Inference for Structured Prediction with Kernels. CoRR abs/2302.10128 (2023) - [i12]Pier Giuseppe Sessa, Pierre Laforgue, Nicolò Cesa-Bianchi, Andreas Krause:
Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning. CoRR abs/2308.01744 (2023) - [i11]Juliette Achddou, Nicolò Cesa-Bianchi, Pierre Laforgue:
Multitask Online Learning: Listen to the Neighborhood Buzz. CoRR abs/2310.17385 (2023) - 2022
- [j1]Nicolò Cesa-Bianchi, Pierre Laforgue, Andrea Paudice, Massimiliano Pontil:
Multitask Online Mirror Descent. Trans. Mach. Learn. Res. 2022 (2022) - [c6]Pierre Laforgue, Giulia Clerici, Nicolò Cesa-Bianchi, Ran Gilad-Bachrach:
A Last Switch Dependent Analysis of Satiation and Seasonality in Bandits. AISTATS 2022: 971-990 - [i10]Tamim El Ahmad, Pierre Laforgue, Florence d'Alché-Buc:
p-Sparsified Sketches for Fast Multiple Output Kernel Methods. CoRR abs/2206.03827 (2022) - [i9]Pierre Laforgue, Stéphan Clémençon, Patrice Bertail:
On Medians of (Randomized) Pairwise Means. CoRR abs/2211.00603 (2022) - 2021
- [c5]Guillaume Staerman, Pierre Laforgue, Pavlo Mozharovskyi, Florence d'Alché-Buc:
When OT meets MoM: Robust estimation of Wasserstein Distance. AISTATS 2021: 136-144 - [c4]Pierre Laforgue, Guillaume Staerman, Stéphan Clémençon:
Generalization Bounds in the Presence of Outliers: a Median-of-Means Study. ICML 2021: 5937-5947 - [i8]Nicolò Cesa-Bianchi, Pierre Laforgue, Andrea Paudice, Massimiliano Pontil:
Multitask Online Mirror Descent. CoRR abs/2106.02393 (2021) - [i7]Robin Vogel, Stéphan Clémençon, Pierre Laforgue:
Visual Recognition with Deep Learning from Biased Image Datasets. CoRR abs/2109.02357 (2021) - [i6]Pierre Laforgue, Giulia Clerici, Nicolò Cesa-Bianchi, Ran Gilad-Bachrach:
Break your Bandit Routine with LSD Rewards: a Last Switch Dependent Analysis of Satiation and Seasonality. CoRR abs/2110.11819 (2021) - 2020
- [c3]Pierre Laforgue, Alex Lambert, Luc Brogat-Motte, Florence d'Alché-Buc:
Duality in RKHSs with Infinite Dimensional Outputs: Application to Robust Losses. ICML 2020: 5598-5607 - [i5]Pierre Laforgue, Guillaume Staerman, Stéphan Clémençon:
How Robust is the Median-of-Means? Concentration Bounds in Presence of Outliers. CoRR abs/2006.05240 (2020) - [i4]Guillaume Staerman, Pierre Laforgue, Pavlo Mozharovskyi, Florence d'Alché-Buc:
When OT meets MoM: Robust estimation of Wasserstein Distance. CoRR abs/2006.10325 (2020)
2010 – 2019
- 2019
- [c2]Pierre Laforgue, Stéphan Clémençon, Florence d'Alché-Buc:
Autoencoding any Data through Kernel Autoencoders. AISTATS 2019: 1061-1069 - [c1]Stéphan Clémençon, Pierre Laforgue, Patrice Bertail:
On Medians of (Randomized) Pairwise Means. ICML 2019: 1272-1281 - [i3]Pierre Laforgue, Stéphan Clémençon:
Statistical Learning from Biased Training Samples. CoRR abs/1906.12304 (2019) - [i2]Pierre Laforgue, Alex Lambert, Luc Motte, Florence d'Alché-Buc:
On the Dualization of Operator-Valued Kernel Machines. CoRR abs/1910.04621 (2019) - 2018
- [i1]Pierre Laforgue, Stéphan Clémençon, Florence d'Alché-Buc:
Autoencoding any Data through Kernel Autoencoders. CoRR abs/1805.11028 (2018)
1970 – 1979
- 1975
- [b1]Pierre Laforgue:
Construction de sous-systèmes utilisant une machine abstraite. Réalisation autour du noyau GEMAU. Grenoble Institute of Technology, France, 1975
Coauthor Index
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