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Yann Guermeur
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2020 – today
- 2023
- [c9]Antoine Ledent, Rodrigo Alves, Yunwen Lei
, Yann Guermeur, Marius Kloft:
Generalization Bounds for Inductive Matrix Completion in Low-Noise Settings. AAAI 2023: 8447-8455 - 2022
- [j15]Antoine Moniot
ProtNAff: protein-bound Nucleic Acid filters and fragment libraries. Bioinform. 38(16): 3911-3917 (2022) - [i4]Antoine Ledent, Rodrigo Alves
Generalization Bounds for Inductive Matrix Completion in Low-noise Settings. CoRR abs/2212.08339 (2022) - 2020
- [j14]Yann Guermeur
Rademacher complexity of margin multi-category classifiers. Neural Comput. Appl. 32(24): 17995-18008 (2020)
2010 – 2019
- 2019
- [j13]Khadija Musayeva, Fabien Lauer
Rademacher complexity and generalization performance of multi-category margin classifiers. Neurocomputing 342: 6-15 (2019) - 2018
- [c8]Khadija Musayeva, Fabien Lauer, Yann Guermeur:
A sharper bound on the Rademacher complexity of margin multi-category classifiers. ESANN 2018 - [i3]Yann Guermeur:
Combinatorial and Structural Results for gamma-Psi-dimensions. CoRR abs/1809.07310 (2018) - 2017
- [j12]Yann Guermeur:
Lp-norm Sauer-Shelah lemma for margin multi-category classifiers. J. Comput. Syst. Sci. 89: 450-473 (2017) - [c7]Yann Guermeur:
Rademacher complexity of margin multi-category classifiers. WSOM 2017: 249-254 - 2014
- [j11]Rémi Bonidal, Samy Tindel, Yann Guermeur:
Model Selection for the ℓ2-SVM by Following the Regularization Path. Trans. Comput. Collect. Intell. 13: 83-112 (2014) - 2012
- [j10]Yann Guermeur:
A generic model of multi-class support vector machine. Int. J. Intell. Inf. Database Syst. 6(6): 555-577 (2012) - [c6]Fabienne Thomarat, Fabien Lauer, Yann Guermeur:
Cascading Discriminant and Generative Models for Protein Secondary Structure Prediction. PRIB 2012: 166-177 - 2011
- [j9]Yann Guermeur, Emmanuel Monfrini:
A Quadratic Loss Multi-Class SVM for which a Radius-Margin Bound Applies. Informatica 22(1): 73-96 (2011) - [j8]Fabien Lauer, Yann Guermeur:
MSVMpack: A Multi-Class Support Vector Machine Package. J. Mach. Learn. Res. 12: 2293-2296 (2011) - [c5]Yann Guermeur, Fabienne Thomarat:
Estimating the Class Posterior Probabilities in Protein Secondary Structure Prediction. PRIB 2011: 260-271
2000 – 2009
- 2008
- [j7]Bernhard Gschloessl, Yann Guermeur, J. Mark Cock
HECTAR: A method to predict subcellular targeting in heterokonts. BMC Bioinform. 9 (2008) - [i2]Emmanuel Monfrini, Yann Guermeur:
A Quadratic Loss Multi-Class SVM. CoRR abs/0804.4898 (2008) - 2007
- [b1]Yann Guermeur:
SVM Multiclasses, Théorie et Applications. (Multi-Class SVMs, Theory and Applications). Henri Poincaré University, Nancy, France, 2007 - [j6]Yann Guermeur:
VC Theory of Large Margin Multi-Category Classifiers. J. Mach. Learn. Res. 8: 2551-2594 (2007) - [i1]Yann Guermeur:
Scale-sensitive Psi-dimensions: the Capacity Measures for Classifiers Taking Values in R^Q. CoRR abs/0706.3679 (2007) - 2006
- [j5]Nicolas Sapay, Yann Guermeur, Gilbert Deléage
Prediction of amphipathic in-plane membrane anchors in monotopic proteins using a SVM classifier. BMC Bioinform. 7: 255 (2006) - 2004
- [j4]Yann Guermeur, Gianluca Pollastri
Combining protein secondary structure prediction models with ensemble methods of optimal complexity. Neurocomputing 56: 305-327 (2004) - 2002
- [j3]Yann Guermeur:
Combining Discriminant Models with New Multi-Class SVMs. Pattern Anal. Appl. 5(2): 168-179 (2002) - 2000
- [c4]Hélène Paugam-Moisy, André Elisseeff, Yann Guermeur:
Generalization Performance of Multiclass Discriminant Models. IJCNN (4) 2000: 177-182 - [c3]Yann Guermeur, André Elisseeff, Hélène Paugam-Moisy:
A New Multi-Class SVM Based on a Uniform Convergence Result. IJCNN (4) 2000: 183-188
1990 – 1999
- 1999
- [j2]Yann Guermeur, Christophe Geourjon, Patrick Gallinari, Gilbert Deléage:
Improved performance in protein secondary structure prediction by inhomogeneous score combination. Bioinform. 15(5): 413-421 (1999) - 1998
- [j1]Olivier Gascuel, Bernadette Bouchon-Meunier, Gilles Caraux, Patrick Gallinari, Alain Guénoche, Yann Guermeur, Yves Lechevallier, Christophe Marsala
Twelve Numerical, Symbolic and Hybrid Supervised Classification Methods. Int. J. Pattern Recognit. Artif. Intell. 12(4): 517-571 (1998) - 1997
- [c2]Yann Guermeur, Florence d'Alché-Buc
Optimal Linear Regression on Classifier Outputs. ICANN 1997: 481-486 - 1996
- [c1]Yann Guermeur, Patrick Gallinari:
Combining Statistical Models for Protein Secondary Structure Prediction. ICANN 1996: 599-604
Coauthor Index
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