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2020 – today
- 2024
[j11]Ismaïl Baaj
, Zied Bouraoui, Antoine Cornuéjols, Thierry Denoeux, Sébastien Destercke, Didier Dubois, Marie-Jeanne Lesot, João Marques-Silva, Jérôme Mengin, Henri Prade, Steven Schockaert, Mathieu Serrurier, Olivier Strauss, Christel Vrain:
Synergies between machine learning and reasoning - An introduction by the Kay R. Amel group. Int. J. Approx. Reason. 171: 109206 (2024)- [c49]Louis Béthune, Thomas Massena, Thibaut Boissin, Aurélien Bellet, Franck Mamalet, Yannick Prudent, Corentin Friedrich, Mathieu Serrurier, David Vigouroux:
DP-SGD Without Clipping: The Lipschitz Neural Network Way. ICLR 2024 - 2023
- [c48]Louis Béthune, Paul Novello, Guillaume Coiffier, Thibaut Boissin, Mathieu Serrurier, Quentin Vincenot, Andres Troya-Galvis:
Robust One-Class Classification with Signed Distance Function using 1-Lipschitz Neural Networks. ICML 2023: 2245-2271 - [c47]Mathieu Serrurier, Franck Mamalet, Thomas Fel, Louis Béthune, Thibaut Boissin:
On the explainable properties of 1-Lipschitz Neural Networks: An Optimal Transport Perspective. NeurIPS 2023 - [i11]Louis Béthune, Paul Novello, Thibaut Boissin, Guillaume Coiffier, Mathieu Serrurier, Quentin Vincenot, Andres Troya-Galvis:
Robust One-Class Classification with Signed Distance Function using 1-Lipschitz Neural Networks. CoRR abs/2303.01978 (2023) - [i10]Louis Béthune, Thomas Massena, Thibaut Boissin, Yannick Prudent, Corentin Friedrich, Franck Mamalet, Aurélien Bellet, Mathieu Serrurier, David Vigouroux:
DP-SGD Without Clipping: The Lipschitz Neural Network Way. CoRR abs/2305.16202 (2023) - 2022
- [c46]Louis Béthune, Thibaut Boissin, Mathieu Serrurier, Franck Mamalet, Corentin Friedrich, Alberto González-Sanz:
Pay attention to your loss : understanding misconceptions about Lipschitz neural networks. NeurIPS 2022 - [i9]Mohamed Chafik Bakkay, Mathieu Serrurier, Valentin Kivachuk Burda, Florian Dupuy, Naty Citlali Cabrera-Gutierrez, Michael Zamo, Maud-Alix Mader, Olivier Mestre, Guillaume Oller, Jean-Christophe Jouhaud, Laurent Terray:
Precipitaion Nowcasting using Deep Neural Network. CoRR abs/2203.13263 (2022) - [i8]Mathieu Serrurier, Franck Mamalet, Thomas Fel, Louis Béthune, Thibaut Boissin:
When adversarial attacks become interpretable counterfactual explanations. CoRR abs/2206.06854 (2022) - 2021
- [c45]Jim Radford, Gilles Richard, Hugo Richard, Mathieu Serrurier:
Detecting Dyslexia from Audio Records: An AI Approach. HEALTHINF 2021: 58-66 - [c44]Mathieu Serrurier, Franck Mamalet, Alberto González-Sanz, Thibaut Boissin, Jean-Michel Loubes, Eustasio del Barrio:
Achieving Robustness in Classification Using Optimal Transport With Hinge Regularization. CVPR 2021: 505-514 - [c43]Achraf Bennis, Sandrine Mouysset, Mathieu Serrurier:
DPWTE: A Deep Learning Approach to Survival Analysis Using a Parsimonious Mixture of Weibull Distributions. ICANN (2) 2021: 185-196 - [i7]Louis Béthune, Alberto González-Sanz, Franck Mamalet, Mathieu Serrurier:
The Many Faces of 1-Lipschitz Neural Networks. CoRR abs/2104.05097 (2021) - 2020
- [c42]Eduardo Hugo Sanchez, Mathieu Serrurier, Mathias Ortner:
Learning Disentangled Representations via Mutual Information Estimation. ECCV (22) 2020: 205-221 - [c41]Achraf Bennis, Sandrine Mouysset, Mathieu Serrurier:
Estimation of Conditional Mixture Weibull Distribution with Right Censored Data Using Neural Network for Time-to-Event Analysis. PAKDD (1) 2020: 687-698 - [c40]Eduardo Hugo Sanchez, Mathieu Serrurier, Mathias Ortner:
Mutual Information Measure for Image Segmentation Using Few Labels. ECML/PKDD (4) 2020: 391-407 - [i6]Gilles Richard, Mathieu Serrurier:
Dyslexia and Dysgraphia prediction: A new machine learning approach. CoRR abs/2005.06401 (2020) - [i5]Mathieu Serrurier, Franck Mamalet, Alberto González-Sanz, Thibaut Boissin, Jean-Michel Loubes, Eustasio del Barrio:
Achieving robustness in classification using optimal transport with hinge regularization. CoRR abs/2006.06520 (2020) - [i4]Jérôme Bolte, Lilian Glaudin, Edouard Pauwels, Mathieu Serrurier:
A Hölderian backtracking method for min-max and min-min problems. CoRR abs/2007.08810 (2020)
2010 – 2019
- 2019
- [j10]Nicolas Hug, Henri Prade, Gilles Richard, Mathieu Serrurier:
Analogical proportion-based methods for recommendation - First investigations. Fuzzy Sets Syst. 366: 110-132 (2019) - [c39]Eduardo Hugo Sanchez, Mathieu Serrurier, Mathias Ortner:
Learning Disentangled Representations of Satellite Image Time Series. ECML/PKDD (3) 2019: 306-321 - [i3]Eduardo Hugo Sanchez, Mathieu Serrurier, Mathias Ortner:
Learning Disentangled Representations of Satellite Image Time Series. CoRR abs/1903.08863 (2019) - [i2]Eduardo Hugo Sanchez, Mathieu Serrurier, Mathias Ortner:
Learning Disentangled Representations via Mutual Information Estimation. CoRR abs/1912.03915 (2019) - [i1]Zied Bouraoui, Antoine Cornuéjols, Thierry Denoeux, Sébastien Destercke, Didier Dubois, Romain Guillaume, João Marques-Silva, Jérôme Mengin, Henri Prade, Steven Schockaert, Mathieu Serrurier, Christel Vrain:
From Shallow to Deep Interactions Between Knowledge Representation, Reasoning and Machine Learning (Kay R. Amel group). CoRR abs/1912.06612 (2019) - 2016
- [c38]Nicolas Hug, Henri Prade, Gilles Richard, Mathieu Serrurier:
Analogical Classifiers: A Theoretical Perspective. ECAI 2016: 689-697 - [c37]Nicolas Hug, Henri Prade, Gilles Richard, Mathieu Serrurier:
Analogy in recommendation. Numerical vs. ordinal: A discussion. FUZZ-IEEE 2016: 2220-2226 - 2015
- [c36]Denis Pallez, Mathieu Serrurier, Célia da Costa Pereira, Giovanni Fusco, Cristina Cao:
Social Specialization of Space: Clustering Households on the French Riviera. GECCO (Companion) 2015: 1447-1448 - [c35]Mathieu Serrurier, Henri Prade:
Entropy evaluation based on confidence intervals of frequency estimates : Application to the learning of decision trees. ICML 2015: 1576-1584 - 2014
- [j9]Myriam Bounhas, Mohammad Ghasemi Hamed, Henri Prade, Mathieu Serrurier, Khaled Mellouli:
Naive possibilistic classifiers for imprecise or uncertain numerical data. Fuzzy Sets Syst. 239: 137-156 (2014) - [c34]Mathieu Serrurier, Henri Prade:
Learning Structure of Bayesian Networks by Using Possibilistic Upper Entropy. SMPS 2014: 87-95 - 2013
- [j8]Mathieu Serrurier, Henri Prade:
An informational distance for estimating the faithfulness of a possibility distribution, viewed as a family of probability distributions, with respect to data. Int. J. Approx. Reason. 54(7): 919-933 (2013) - [j7]Myriam Bounhas, Khaled Mellouli, Henri Prade, Mathieu Serrurier:
Possibilistic classifiers for numerical data. Soft Comput. 17(5): 733-751 (2013) - [c33]Gwenael Bothorel, Mathieu Serrurier, Christophe Hurter:
Visualization of Frequent Itemsets with Nested Circular Layout and Bundling Algorithm. ISVC (2) 2013: 396-405 - [c32]Gwenael Bothorel, Mathieu Serrurier, Christophe Hurter:
From Visualization to Association Rules: an automatic approach. SCCG 2013: 57-64 - [c31]Mathieu Serrurier, Henri Prade:
A Scalable Learning Algorithm for Kernel Probabilistic Classifier. SUM 2013: 297-310 - 2012
- [c30]Mohammad Ghasemi Hamed, Mathieu Serrurier, Nicolas Durand:
Simultaneous Interval Regression for K-Nearest Neighbor. Australasian Conference on Artificial Intelligence 2012: 602-613 - [c29]Myriam Bounhas, Henri Prade, Mathieu Serrurier, Khaled Mellouli:
A Possibilistic Rule-Based Classifier. IPMU (1) 2012: 21-31 - [c28]Mohammad Ghasemi Hamed, Mathieu Serrurier, Nicolas Durand:
Possibilistic KNN Regression Using Tolerance Intervals. IPMU (3) 2012: 410-419 - [c27]Mathieu Serrurier, Henri Prade:
Classification Based on Possibilistic Likelihood. IPMU (3) 2012: 420-429 - [c26]Mohammad Ghasemi Hamed, Mathieu Serrurier, Nicolas Durand:
Representing Uncertainty by Possibility Distributions Encoding Confidence Bands, Tolerance and Prediction Intervals. SUM 2012: 233-246 - 2011
- [c25]Myriam Bounhas, Henri Prade, Mathieu Serrurier, Khaled Mellouli:
Possibilistic Classifiers for Uncertain Numerical Data. ECSQARU 2011: 434-446 - [c24]Mathieu Serrurier, Henri Prade:
Maximum-likelihood principle for possibility distributions viewed as families of probabilities. FUZZ-IEEE 2011: 2987-2993 - [c23]Gwenael Bothorel, Mathieu Serrurier, Christophe Hurter:
Utilisation d'outils de visual data mining pour l'exploration d'un ensemble de règles d'association. IHM 2011: 12:1-12:4 - [c22]Mathieu Serrurier, Henri Prade:
Imprecise Regression Based on Possibilistic Likelihood. SUM 2011: 447-459 - 2010
- [c21]Christophe Hurter, Mathieu Serrurier, Roland Alonso, Gilles Tabart, Jean-Luc Vinot:
An automatic generation of schematic maps to display flight routes for air traffic controllers: structure and color optimization. AVI 2010: 233-240 - [c20]Henri Prade, Mathieu Serrurier:
Why Imprecise Regression: A Discussion. SMPS 2010: 527-535 - [c19]Myriam Bounhas, Khaled Mellouli, Henri Prade, Mathieu Serrurier:
From Bayesian Classifiers to Possibilistic Classifiers for Numerical Data. SUM 2010: 112-125
2000 – 2009
- 2009
- [c18]Henri Prade, Agnès Rico, Mathieu Serrurier, Eric Raufaste:
Elicitating Sugeno Integrals: Methodology and a Case Study. ECSQARU 2009: 712-723 - [c17]Christophe Hurter, Mathieu Serrurier, Gilles Tabart, Jean-Luc Vinot:
Génération et placement de couleurs sur une vue de type métro. IHM 2009: 55-58 - [c16]Henri Prade, Agnès Rico, Mathieu Serrurier:
Elicitation of Sugeno Integrals: A Version Space Learning Perspective. ISMIS 2009: 392-401 - 2008
- [j6]Leila Amgoud, Mathieu Serrurier:
Agents that argue and explain classifications. Auton. Agents Multi Agent Syst. 16(2): 187-209 (2008) - [j5]Henri Prade, Mathieu Serrurier:
Bipolar version space learning. Int. J. Intell. Syst. 23(10): 1135-1152 (2008) - [j4]Mathieu Serrurier, Henri Prade:
Improving inductive logic programming by using simulated annealing. Inf. Sci. 178(6): 1423-1441 (2008) - 2007
- [j3]Mathieu Serrurier, Henri Prade:
Introducing possibilistic logic in ILP for dealing with exceptions. Artif. Intell. 171(16-17): 939-950 (2007) - [j2]Mathieu Serrurier, Didier Dubois, Henri Prade, Thomas A. Sudkamp:
Learning fuzzy rules with their implication operators. Data Knowl. Eng. 60(1): 71-89 (2007) - [j1]Mathieu Serrurier, Henri Prade:
Improving Expressivity of Inductive Logic Programming by Learning Different Kinds of Fuzzy Rules. Soft Comput. 11(5): 459-466 (2007) - [c15]Leila Amgoud, Mathieu Serrurier:
Arguing and Explaining Classifications. ArgMAS 2007: 164-177 - [c14]Leila Amgoud, Mathieu Serrurier:
Arguing and explaining classifications. AAMAS 2007: 160 - [c13]Mathieu Serrurier, Henri Prade:
A General Framework for Imprecise Regression. FUZZ-IEEE 2007: 1-6 - [c12]Mathieu Raynal, Mathieu Serrurier:
Loi de fitts: prédiction du temps de pointage sous forme d'ensembles flous. IHM 2007: 3-10 - 2006
- [c11]Henri Prade, Mathieu Serrurier:
Version Space Learning for Possibilistic Hypotheses. ECAI 2006: 801-802 - [c10]Mathieu Serrurier, Henri Prade:
Imprecise Regression and Regression on Fuzzy Data - A Preliminary Discussion. FUZZ-IEEE 2006: 1506-1511 - 2005
- [c9]Mathieu Serrurier, Henri Prade:
Possibilistic Inductive Logic Programming. ECSQARU 2005: 675-686 - [c8]Mathieu Serrurier, Thomas A. Sudkamp, Didier Dubois, Henri Prade:
Fuzzy Inductive Logic Programming: Learning Fuzzy Rules with their Implication. FUZZ-IEEE 2005: 613-618 - [c7]Mathieu Serrurier, Henri Prade:
Coping with exceptions in multiclass ILP problems using possibilistic logic. IJCAI 2005: 1761- - 2004
- [c6]Henri Prade, Mathieu Serrurier:
Getting adaptability or expressivity in inductive logic programming by using fuzzy predicates. FUZZ-IEEE 2004: 73-77 - [c5]Mathieu Serrurier, Henri Prade, Gilles Richard:
A Simulated Annealing Framework for ILP. ILP 2004: 288-304 - 2003
- [c4]Henri Prade, Gilles Richard, Mathieu Serrurier:
On the Induction of Different Kinds of First-Order Fuzzy Rules. ECSQARU 2003: 370-381 - [c3]Henri Prade, Gilles Richard, Mathieu Serrurier:
Learning First Order Fuzzy Logic Rules. IFSA 2003: 702-709 - [c2]Henri Prade, Gilles Richard, Mathieu Serrurier:
Enriching Relational Learning with Fuzzy Predicates. PKDD 2003: 399-410 - 2002
- [c1]Mathieu Raynal, Mathieu Serrurier:
CYNTHIA: An HTML Browser for Visually Handicapped People. ICCHP 2002: 353-359
Coauthor Index
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