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Benjamin Guedj
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2020 – today
- 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) - [c22]Fredrik Hellström, Benjamin Guedj:
Comparing Comparators in Generalization Bounds. AISTATS 2024: 73-81 - [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) - [j14]Arthur Leroy, Pierre Latouche, Benjamin Guedj, Servane Gey:
Cluster-Specific Predictions with Multi-Task Gaussian Processes. J. Mach. Learn. Res. 24: 5:1-5:49 (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) - [i48]Fredrik Hellström, Giuseppe Durisi, Benjamin Guedj, Maxim Raginsky:
Generalization Bounds: Perspectives from Information Theory and PAC-Bayes. CoRR abs/2309.04381 (2023) - [i47]Fredrik Hellström, Benjamin Guedj:
Comparing Comparators in Generalization Bounds. CoRR abs/2310.10534 (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
- [j11]Arthur Leroy
, Pierre Latouche, Benjamin Guedj
, Servane Gey:
MAGMA: inference and prediction using multi-task Gaussian processes with common mean. Mach. Learn. 111(5): 1821-1849 (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 - [c17]Antoine Vendeville, Anastasios Giovanidis, Effrosyni Papanastasiou, Benjamin Guedj
:
Opening up Echo Chambers via Optimal Content Recommendation. COMPLEX NETWORKS (1) 2022: 74-85 - [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) - [i41]Antoine Picard-Weibel, Benjamin Guedj:
On change of measure inequalities for f-divergences. CoRR abs/2202.05568 (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) - [i38]Antoine Vendeville, Benjamin Guedj, Shi Zhou:
Depolarising Social Networks: Optimisation of Exposure to Adverse Opinions in the Presence of a Backfire Effect. CoRR abs/2203.02002 (2022) - [i37]Jiale Wei, Qiyuan Chen, Pai Peng, Benjamin Guedj, Le Li:
Reprint: a randomized extrapolation based on principal components for data augmentation. CoRR abs/2204.12024 (2022) - [i36]Maxime Haddouche, Benjamin Guedj
:
Online PAC-Bayes Learning. CoRR abs/2206.00024 (2022) - [i35]Antoine Vendeville, Anastasios Giovanidis, Effrosyni Papanastasiou, Benjamin Guedj:
Opening up echo chambers via optimal content recommendation. CoRR abs/2206.03859 (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
- [j10]Antoine Vendeville
, Benjamin Guedj
, Shi Zhou:
Forecasting elections results via the voter model with stubborn nodes. Appl. Netw. Sci. 6(1): 1 (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) - [j7]Benjamin Guedj
, Louis Pujol
:
Still No Free Lunches: The Price to Pay for Tighter PAC-Bayes Bounds. Entropy 23(11): 1529 (2021) - [j6]Le Li
, Benjamin Guedj
:
Sequential Learning of Principal Curves: Summarizing Data Streams on the Fly. Entropy 23(11): 1534 (2021) - [c10]Vincent Cohen-Addad, Benjamin Guedj, Varun Kanade, Guy Rom:
Online k-means Clustering. AISTATS 2021: 1126-1134 - [c9]Antoine Vendeville
, Benjamin Guedj
, Shi Zhou:
Towards Control of Opinion Diversity by Introducing Zealots into a Polarised Social Group. COMPLEX NETWORKS 2021: 341-352 - [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
- [j5]Pierre Alliez, Roberto Di Cosmo, Benjamin Guedj
, Alain Girault, Mohand-Saïd Hacid, Arnaud Legrand, Nicolas P. Rougier:
Attributing and Referencing (Research) Software: Best Practices and Outlook From Inria. Comput. Sci. Eng. 22(1): 39-52 (2020) - [j4]Benjamin Guedj
, Bhargav Srinivasa Desikan:
Kernel-Based Ensemble Learning in Python. Inf. 11(2): 63 (2020) - [c7]Stéphane Chrétien
, Benjamin Guedj
:
Revisiting Clustering as Matrix Factorisation on the Stiefel Manifold. LOD (1) 2020: 1-12 - [c6]Zakaria Mhammedi, Benjamin Guedj, Robert C. Williamson:
PAC-Bayesian Bound for the Conditional Value at Risk. NeurIPS 2020 - [c5]Benjamin Guedj
, Juliette Rengot:
Non-linear Aggregation of Filters to Improve Image Denoising. SAI (2) 2020: 314-327 - [c4]Kento Nozawa, Pascal Germain, Benjamin Guedj:
PAC-Bayesian Contrastive Unsupervised Representation Learning. UAI 2020: 21-30 - [i24]Florent Dewez
, Benjamin Guedj, Vincent Vandewalle:
From industry-wide parameters to aircraft-centric on-flight inference: improving aeronautics performance prediction with machine learning. CoRR abs/2005.05286 (2020) - [i23]Antoine Vendeville, Benjamin Guedj, Shi Zhou:
How opinions crystallise: an analysis of polarisation in the voter model. CoRR abs/2006.07265 (2020) - [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) - [i19]Arthur Leroy
, Pierre Latouche, Benjamin Guedj, Servane Gey:
MAGMA: Inference and Prediction with Multi-Task Gaussian Processes. CoRR abs/2007.10731 (2020) - [i18]Antoine Vendeville, Benjamin Guedj, Shi Zhou:
Forecasting elections results via the voter model with stubborn nodes. CoRR abs/2009.10627 (2020) - [i17]Arthur Leroy
, Pierre Latouche, Benjamin Guedj, Servane Gey:
Cluster-Specific Predictions with Multi-Task Gaussian Processes. CoRR abs/2011.07866 (2020) - [i16]Florent Dewez
, Benjamin Guedj, Arthur Talpaert, Vincent Vandewalle:
An end-to-end data-driven optimisation framework for constrained trajectories. CoRR abs/2011.11820 (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)
2010 – 2019
- 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 - [c1]John Klein
, Mahmoud Albardan, Benjamin Guedj
, Olivier Colot
:
Decentralized Learning with Budgeted Network Load Using Gaussian Copulas and Classifier Ensembles. PKDD/ECML Workshops (1) 2019: 301-316 - [i13]Benjamin Guedj
:
A Primer on PAC-Bayesian Learning. CoRR abs/1901.05353 (2019) - [i12]Stéphane Chrétien, Benjamin Guedj:
Revisiting clustering as matrix factorisation on the Stiefel manifold. CoRR abs/1903.04479 (2019) - [i11]Benjamin Guedj
, Juliette Rengot:
Non-linear aggregation of filters to improve image denoising. CoRR abs/1904.00865 (2019) - [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) - [i8]Pierre Alliez, Roberto Di Cosmo, Benjamin Guedj
, Alain Girault, Mohand-Said Hacid, Arnaud Legrand, Nicolas P. Rougier:
Attributing and Referencing (Research) Software: Best Practices and Outlook from Inria. CoRR abs/1905.11123 (2019) - [i7]Zakaria Mhammedi, Peter D. Grünwald, Benjamin Guedj
:
PAC-Bayes Un-Expected Bernstein Inequality. CoRR abs/1905.13367 (2019) - [i6]Vincent Cohen-Addad, Benjamin Guedj
, Varun Kanade, Guy Rom:
Online k-means Clustering. CoRR abs/1909.06861 (2019) - [i5]Benjamin Guedj
, Louis Pujol:
Still no free lunches: the price to pay for tighter PAC-Bayes bounds. CoRR abs/1910.04460 (2019) - [i4]Kento Nozawa
, Pascal Germain, Benjamin Guedj
:
PAC-Bayesian Contrastive Unsupervised Representation Learning. CoRR abs/1910.04464 (2019) - [i3]Benjamin Guedj, Bhargav Srinivasa Desikan:
Kernel-Based Ensemble Learning in Python. CoRR abs/1912.08311 (2019) - 2018
- [j3]Pierre Alquier
, Benjamin Guedj
:
Simpler PAC-Bayesian bounds for hostile data. Mach. Learn. 107(5): 887-902 (2018) - [i2]John Klein, Mahmoud Albardan, Benjamin Guedj
, Olivier Colot:
Decentralized learning with budgeted network load using Gaussian copulas and classifier ensembles. CoRR abs/1804.10028 (2018) - [i1]Benjamin Guedj
, Le Li:
Sequential Learning of Principal Curves: Summarizing Data Streams on the Fly. CoRR abs/1805.07418 (2018) - 2017
- [j2]Benjamin Guedj, Bhargav Srinivasa Desikan:
Pycobra: A Python Toolbox for Ensemble Learning and Visualisation. J. Mach. Learn. Res. 18: 190:1-190:5 (2017) - 2016
- [j1]Gérard Biau, Aurélie Fischer, Benjamin Guedj
, James D. Malley:
COBRA: A combined regression strategy. J. Multivar. Anal. 146: 18-28 (2016)
Coauthor Index
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last updated on 2024-08-10 01:26 CEST by the dblp team
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