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2020 – today
- 2024
[i3]Kylliann De Santiago, Marie Szafranski, Christophe Ambroise:
Mixture of multilayer stochastic block models for multiview clustering. CoRR abs/2401.04682 (2024)- 2023
- [b2]Marie Szafranski:
Apprentissage machine pour l'intégration et l'interaction de données structurées. (: The adventures of struct ured {int* a_ctions} in Dataland). University of Paris-Saclay, France, 2023 - [c7]Kylliann De Santiago, Marie Szafranski, Christophe Ambroise:
Mixture of stochastic block models for multiview clustering. ESANN 2023 - 2020
- [j5]Florent Guinot, Marie Szafranski
, Julien Chiquet, Anouk Zancarini, Christine Le Signor, Christophe Mougel, Christophe Ambroise:
Fast computation of genome-metagenome interaction effects. Algorithms Mol. Biol. 15(1): 13 (2020)
2010 – 2019
- 2018
- [j4]Florent Guinot, Marie Szafranski, Christophe Ambroise, Franck Samson:
Learning the optimal scale for GWAS through hierarchical SNP aggregation. BMC Bioinform. 19(1): 459:1-459:14 (2018) - [i2]Florent Guinot, Marie Szafranski, Julien Chiquet, Anouk Zancarini, Christine Le Signor, Christophe Mougel, Christophe Ambroise:
Fast Computation of Genome-Metagenome Interaction Effects. CoRR abs/1810.12169 (2018) - 2016
- [j3]Céline Brouard, Marie Szafranski, Florence d'Alché-Buc:
Input Output Kernel Regression: Supervised and Semi-Supervised Structured Output Prediction with Operator-Valued Kernels. J. Mach. Learn. Res. 17: 176:1-176:48 (2016) - 2014
- [c6]Marie Szafranski, Yves Grandvalet:
KEOPS: Kernels organized into pyramids. ICASSP 2014: 8262-8266 - 2011
- [c5]Céline Brouard, Florence d'Alché-Buc, Marie Szafranski:
Semi-supervised Penalized Output Kernel Regression for Link Prediction. ICML 2011: 593-600 - 2010
- [j2]Liva Ralaivola, Marie Szafranski, Guillaume Stempfel:
Chromatic PAC-Bayes Bounds for Non-IID Data: Applications to Ranking and Stationary β-Mixing Processes. J. Mach. Learn. Res. 11: 1927-1956 (2010) - [j1]Marie Szafranski, Yves Grandvalet, Alain Rakotomamonjy:
Composite kernel learning. Mach. Learn. 79(1-2): 73-103 (2010)
2000 – 2009
- 2009
- [c4]Matthieu Kowalski, Marie Szafranski, Liva Ralaivola:
Multiple indefinite kernel learning with mixed norm regularization. ICML 2009: 545-552 - [c3]Liva Ralaivola, Marie Szafranski, Guillaume Stempfel:
Chromatic PAC-Bayes Bounds for Non-IID Data. AISTATS 2009: 416-423 - [i1]Liva Ralaivola, Marie Szafranski, Guillaume Stempfel:
Chromatic PAC-Bayes Bounds for Non-IID Data: Applications to Ranking and Stationary \beta-Mixing Processes. CoRR abs/0909.1933 (2009) - 2008
- [b1]Marie Szafranski:
Pénalités hiérarchiques pour l'intégration de connaissances dans les modèles statistiques. (Hierarchical penalties for integrating prior knowledge in statistical models). University of Technology of Compiègne, France, 2008 - [c2]Marie Szafranski, Yves Grandvalet, Alain Rakotomamonjy:
Composite kernel learning. ICML 2008: 1040-1047 - 2007
- [c1]Marie Szafranski, Yves Grandvalet, Pierre Morizet-Mahoudeaux:
Hierarchical Penalization. NIPS 2007: 1457-1464
Coauthor Index
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