default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDBenjamin Guedj
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
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 - [i55]Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj:
Tighter Generalisation Bounds via Interpolation. CoRR abs/2402.05101 (2024) - [i54]Maxime Haddouche, Paul Viallard, Umut Simsekli, Benjamin Guedj:
A PAC-Bayesian Link Between Generalisation and Flat Minima. CoRR abs/2402.08508 (2024) - [i53]Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi:
Closed-form Filtering for Non-linear Systems. CoRR abs/2402.09796 (2024) - [i52]Chloé Hashimoto-Cullen, Benjamin Guedj:
Predicting Electricity Consumption with Random Walks on Gaussian Processes. CoRR abs/2409.05934 (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
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-10 22:18 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
