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Benjamin Guedj
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Publications
- 2024
- [j16]Eugenio Clerico, Benjamin Guedj:
A note on regularised NTK dynamics with an application to PAC-Bayesian training. Trans. Mach. Learn. Res. 2024 (2024) - [i54]Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj:
Tighter Generalisation Bounds via Interpolation. CoRR abs/2402.05101 (2024) - [i53]Maxime Haddouche, Paul Viallard, Umut Simsekli, Benjamin Guedj:
A PAC-Bayesian Link Between Generalisation and Flat Minima. CoRR abs/2402.08508 (2024) - [i52]Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi:
Closed-form Filtering for Non-linear Systems. CoRR abs/2402.09796 (2024) - 2023
- [j15]Jie M. Zhang, Mark Harman, Benjamin Guedj, Earl T. Barr, John Shawe-Taylor:
Model validation using mutated training labels: An exploratory study. Neurocomputing 539: 126116 (2023) - [j13]Antonin Schrab, Ilmun Kim, Mélisande Albert, Béatrice Laurent, Benjamin Guedj, Arthur Gretton:
MMD Aggregated Two-Sample Test. J. Mach. Learn. Res. 24: 194:1-194:81 (2023) - [j12]Maxime Haddouche, Benjamin Guedj:
PAC-Bayes Generalisation Bounds for Heavy-Tailed Losses through Supermartingales. Trans. Mach. Learn. Res. 2023 (2023) - [c21]Felix Biggs, Benjamin Guedj:
Tighter PAC-Bayes Generalisation Bounds by Leveraging Example Difficulty. AISTATS 2023: 8165-8182 - [c20]Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj:
Learning via Wasserstein-Based High Probability Generalisation Bounds. NeurIPS 2023 - [i51]Maxime Haddouche, Benjamin Guedj, Olivier Wintenberger:
Optimistic Dynamic Regret Bounds. CoRR abs/2301.07530 (2023) - [i50]Maxime Haddouche, Benjamin Guedj:
Wasserstein PAC-Bayes Learning: A Bridge Between Generalisation and Optimisation. CoRR abs/2304.07048 (2023) - [i49]Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj:
Learning via Wasserstein-Based High Probability Generalisation Bounds. CoRR abs/2306.04375 (2023) - [i46]Pierre Jobic, Maxime Haddouche, Benjamin Guedj:
Federated Learning with Nonvacuous Generalisation Bounds. CoRR abs/2310.11203 (2023) - [i45]Eugenio Clerico, Benjamin Guedj:
A note on regularised NTK dynamics with an application to PAC-Bayesian training. CoRR abs/2312.13259 (2023) - 2022
- [c19]Badr-Eddine Chérief-Abdellatif, Yuyang Shi, Arnaud Doucet, Benjamin Guedj:
On PAC-Bayesian reconstruction guarantees for VAEs. AISTATS 2022: 3066-3079 - [c18]Felix Biggs, Benjamin Guedj:
On Margins and Derandomisation in PAC-Bayes. AISTATS 2022: 3709-3731 - [c16]Felix Biggs, Benjamin Guedj:
Non-Vacuous Generalisation Bounds for Shallow Neural Networks. ICML 2022: 1963-1981 - [c15]Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi:
Measuring dissimilarity with diffeomorphism invariance. ICML 2022: 2572-2596 - [c14]Felix Biggs, Valentina Zantedeschi, Benjamin Guedj:
On Margins and Generalisation for Voting Classifiers. NeurIPS 2022 - [c13]Maxime Haddouche, Benjamin Guedj:
Online PAC-Bayes Learning. NeurIPS 2022 - [c12]Antonin Schrab, Benjamin Guedj, Arthur Gretton:
KSD Aggregated Goodness-of-fit Test. NeurIPS 2022 - [c11]Antonin Schrab, Ilmun Kim, Benjamin Guedj, Arthur Gretton:
Efficient Aggregated Kernel Tests using Incomplete $U$-statistics. NeurIPS 2022 - [i44]Antonin Schrab, Benjamin Guedj, Arthur Gretton:
KSD Aggregated Goodness-of-fit Test. CoRR abs/2202.00824 (2022) - [i43]Felix Biggs, Benjamin Guedj:
Non-Vacuous Generalisation Bounds for Shallow Neural Networks. CoRR abs/2202.01627 (2022) - [i42]Reuben Adams, John Shawe-Taylor, Benjamin Guedj:
Controlling Confusion via Generalisation Bounds. CoRR abs/2202.05560 (2022) - [i40]Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi:
Measuring dissimilarity with diffeomorphism invariance. CoRR abs/2202.05614 (2022) - [i39]Badr-Eddine Chérief-Abdellatif, Yuyang Shi, Arnaud Doucet, Benjamin Guedj:
On PAC-Bayesian reconstruction guarantees for VAEs. CoRR abs/2202.11455 (2022) - [i36]Maxime Haddouche, Benjamin Guedj:
Online PAC-Bayes Learning. CoRR abs/2206.00024 (2022) - [i34]Felix Biggs, Valentina Zantedeschi, Benjamin Guedj:
On Margins and Generalisation for Voting Classifiers. CoRR abs/2206.04607 (2022) - [i33]Antonin Schrab, Ilmun Kim, Benjamin Guedj, Arthur Gretton:
Efficient Aggregated Kernel Tests using Incomplete U-statistics. CoRR abs/2206.09194 (2022) - [i32]Eugenio Clerico, George Deligiannidis, Benjamin Guedj, Arnaud Doucet:
A PAC-Bayes bound for deterministic classifiers. CoRR abs/2209.02525 (2022) - [i31]Maxime Haddouche, Benjamin Guedj:
PAC-Bayes with Unbounded Losses through Supermartingales. CoRR abs/2210.00928 (2022) - [i30]Felix Biggs, Benjamin Guedj:
Tighter PAC-Bayes Generalisation Bounds by Leveraging Example Difficulty. CoRR abs/2210.11289 (2022) - 2021
- [j9]Felix Biggs, Benjamin Guedj:
Differentiable PAC-Bayes Objectives with Partially Aggregated Neural Networks. Entropy 23(10): 1280 (2021) - [j8]Maxime Haddouche, Benjamin Guedj, Omar Rivasplata, John Shawe-Taylor:
PAC-Bayes Unleashed: Generalisation Bounds with Unbounded Losses. Entropy 23(10): 1330 (2021) - [c8]Valentina Zantedeschi, Paul Viallard, Emilie Morvant, Rémi Emonet, Amaury Habrard, Pascal Germain, Benjamin Guedj:
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound. NeurIPS 2021: 455-467 - [i29]Valentina Zantedeschi, Paul Viallard, Emilie Morvant, Rémi Emonet, Amaury Habrard, Pascal Germain, Benjamin Guedj:
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound. CoRR abs/2106.12535 (2021) - [i28]Felix Biggs, Benjamin Guedj:
On Margins and Derandomisation in PAC-Bayes. CoRR abs/2107.03955 (2021) - [i27]María Pérez-Ortiz, Omar Rivasplata, Benjamin Guedj, Matthew Gleeson, Jingyu Zhang, John Shawe-Taylor, Miroslaw Bober, Josef Kittler:
Learning PAC-Bayes Priors for Probabilistic Neural Networks. CoRR abs/2109.10304 (2021) - [i26]Antonin Schrab, Ilmun Kim, Mélisande Albert, Béatrice Laurent, Benjamin Guedj, Arthur Gretton:
MMD Aggregated Two-Sample Test. CoRR abs/2110.15073 (2021) - [i25]María Pérez-Ortiz, Omar Rivasplata, Emilio Parrado-Hernández, Benjamin Guedj, John Shawe-Taylor:
Progress in Self-Certified Neural Networks. CoRR abs/2111.07737 (2021) - 2020
- [c6]Zakaria Mhammedi, Benjamin Guedj, Robert C. Williamson:
PAC-Bayesian Bound for the Conditional Value at Risk. NeurIPS 2020 - [c4]Kento Nozawa, Pascal Germain, Benjamin Guedj:
PAC-Bayesian Contrastive Unsupervised Representation Learning. UAI 2020: 21-30 - [i22]Maxime Haddouche, Benjamin Guedj, Omar Rivasplata, John Shawe-Taylor:
PAC-Bayes unleashed: generalisation bounds with unbounded losses. CoRR abs/2006.07279 (2020) - [i21]Felix Biggs, Benjamin Guedj:
Differentiable PAC-Bayes Objectives with Partially Aggregated Neural Networks. CoRR abs/2006.12228 (2020) - [i20]Zakaria Mhammedi, Benjamin Guedj, Robert C. Williamson:
PAC-Bayesian Bound for the Conditional Value at Risk. CoRR abs/2006.14763 (2020) - [i15]Théophile Cantelobre, Benjamin Guedj, María Pérez-Ortiz, John Shawe-Taylor:
A PAC-Bayesian Perspective on Structured Prediction with Implicit Loss Embeddings. CoRR abs/2012.03780 (2020) - [i14]Maxime Haddouche, Benjamin Guedj, Omar Rivasplata, John Shawe-Taylor:
Upper and Lower Bounds on the Performance of Kernel PCA. CoRR abs/2012.10369 (2020) - 2019
- [c3]Gaël Letarte, Pascal Germain, Benjamin Guedj, François Laviolette:
Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks. NeurIPS 2019: 6869-6879 - [c2]Zakaria Mhammedi, Peter Grünwald, Benjamin Guedj:
PAC-Bayes Un-Expected Bernstein Inequality. NeurIPS 2019: 12180-12191 - [i10]Jie M. Zhang, Earl T. Barr, Benjamin Guedj, Mark Harman, John Shawe-Taylor:
Perturbed Model Validation: A New Framework to Validate Model Relevance. CoRR abs/1905.10201 (2019) - [i9]Gaël Letarte, Pascal Germain, Benjamin Guedj, François Laviolette:
Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks. CoRR abs/1905.10259 (2019) - [i7]Zakaria Mhammedi, Peter D. Grünwald, Benjamin Guedj:
PAC-Bayes Un-Expected Bernstein Inequality. CoRR abs/1905.13367 (2019) - [i4]Kento Nozawa, Pascal Germain, Benjamin Guedj:
PAC-Bayesian Contrastive Unsupervised Representation Learning. CoRR abs/1910.04464 (2019) - 2018
- [j3]Pierre Alquier, Benjamin Guedj:
Simpler PAC-Bayesian bounds for hostile data. Mach. Learn. 107(5): 887-902 (2018) - 2016
- [j1]Gérard Biau, Aurélie Fischer, Benjamin Guedj, James D. Malley:
COBRA: A combined regression strategy. J. Multivar. Anal. 146: 18-28 (2016)
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last updated on 2024-09-13 01:41 CEST by the dblp team
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