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André Elisseeff
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2010 – 2019
- 2012
- [i1]Ulf H. Nielsen, Jean-Philippe Pellet, André Elisseeff:
Explanation Trees for Causal Bayesian Networks. CoRR abs/1206.3276 (2012) - 2010
- [j13]Giuseppe Paleologo, André Elisseeff, Gianluca Antonini:
Subagging for credit scoring models. Eur. J. Oper. Res. 201(2): 490-499 (2010) - [j12]André Elisseeff, Jean-Philippe Pellet
, Eleni Pratsini:
Causal networks for risk and compliance: Methodology and application. IBM J. Res. Dev. 54(3): 6 (2010)
2000 – 2009
- 2008
- [j11]Jean-Philippe Pellet, André Elisseeff:
Using Markov Blankets for Causal Structure Learning. J. Mach. Learn. Res. 9: 1295-1342 (2008) - [c15]Jean-Philippe Pellet, André Elisseeff:
Finding Latent Causes in Causal Networks: an Efficient Approach Based on Markov Blankets. NIPS 2008: 1249-1256 - [c14]Ulf H. Nielsen, Jean-Philippe Pellet, André Elisseeff:
Explanation Trees for Causal Bayesian Networks. UAI 2008: 427-434 - [c13]Isabelle Guyon, Constantin F. Aliferis, Gregory F. Cooper, André Elisseeff, Jean-Philippe Pellet, Peter Spirtes, Alexander R. Statnikov:
Design and Analysis of the Causation and Prediction Challenge. WCCI Causation and Prediction Challenge 2008: 1-33 - [e1]Isabelle Guyon, Constantin F. Aliferis, Gregory F. Cooper, André Elisseeff, Jean-Philippe Pellet, Peter Spirtes, Alexander R. Statnikov:
Causation and Prediction Challenge at WCCI 2008, Hong Kong, June 1-6, 2008. JMLR Proceedings 3, JMLR.org 2008 [contents] - 2007
- [j10]Olivier Bousquet, André Elisseeff:
Guest editorial: Learning theory. Mach. Learn. 66(2-3): 115-118 (2007) - [c12]Jean-Philippe Pellet
A Partial Correlation-Based Algorithm for Causal Structure Discovery with Continuous Variables. IDA 2007: 229-239 - 2006
- [p2]Isabelle Guyon, André Elisseeff:
An Introduction to Feature Extraction. Feature Extraction 2006: 1-25 - [p1]Thomas Navin Lal, Olivier Chapelle, Jason Weston, André Elisseeff:
Embedded Methods. Feature Extraction 2006: 137-165 - 2005
- [j9]Jason Weston, Christina S. Leslie, Eugene Ie, Dengyong Zhou, André Elisseeff, William Stafford Noble:
Semi-supervised protein classification using cluster kernels. Bioinform. 21(15): 3241-3247 (2005) - [j8]André Elisseeff, Theodoros Evgeniou, Massimiliano Pontil:
Stability of Randomized Learning Algorithms. J. Mach. Learn. Res. 6: 55-79 (2005) - [c11]Giuliano Tirenni, Abderrahim Labbi, André Elisseeff, Cesar Berrospi:
Efficient Allocation of Marketing Resources using Dynamic Programming. SDM 2005: 581-585 - 2004
- [j7]Yann Guermeur, Gianluca Pollastri
Combining protein secondary structure prediction models with ensemble methods of optimal complexity. Neurocomputing 56: 305-327 (2004) - [j6]Theodoros Evgeniou, Massimiliano Pontil, André Elisseeff:
Leave One Out Error, Stability, and Generalization of Voting Combinations of Classifiers. Mach. Learn. 55(1): 71-97 (2004) - 2003
- [j5]Jason Weston, Fernando Pérez-Cruz
Feature selection and transduction for prediction of molecular bioactivity for drug design. Bioinform. 19(6): 764-771 (2003) - [j4]Isabelle Guyon, André Elisseeff:
An Introduction to Variable and Feature Selection. J. Mach. Learn. Res. 3: 1157-1182 (2003) - [j3]Jason Weston, André Elisseeff, Bernhard Schölkopf, Michael E. Tipping:
Use of the Zero-Norm with Linear Models and Kernel Methods. J. Mach. Learn. Res. 3: 1439-1461 (2003) - [c10]Jason Weston, Christina S. Leslie, Dengyong Zhou, André Elisseeff, William Stafford Noble:
Semi-supervised Protein Classification Using Cluster Kernels. NIPS 2003: 595-602 - 2002
- [j2]Olivier Bousquet, André Elisseeff:
Stability and Generalization. J. Mach. Learn. Res. 2: 499-526 (2002) - [c9]Savina Andonova, André Elisseeff, Theodoros Evgeniou, Massimiliano Pontil:
A Simple Algorithm for Learning Stable Machines. ECAI 2002: 513-517 - [c8]Jason Weston, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf, Vladimir Vapnik:
Kernel Dependency Estimation. NIPS 2002: 873-880 - [c7]Asa Ben-Hur, André Elisseeff, Isabelle Guyon:
A Stability Based Method for Discovering Structure in Clustered Data. Pacific Symposium on Biocomputing 2002: 6-17 - 2001
- [c6]Nello Cristianini, John Shawe-Taylor, André Elisseeff, Jaz S. Kandola:
On Kernel-Target Alignment. NIPS 2001: 367-373 - [c5]André Elisseeff, Jason Weston:
A kernel method for multi-labelled classification. NIPS 2001: 681-687 - 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 - [c2]Olivier Bousquet, André Elisseeff:
Algorithmic Stability and Generalization Performance. NIPS 2000: 196-202
1990 – 1999
- 1999
- [j1]André Elisseeff, Hélène Paugam-Moisy:
JNN, a randomized algorithm for training multilayer networks in polynomial time. Neurocomputing 29(1-3): 3-24 (1999) - 1996
- [c1]André Elisseeff, Hélène Paugam-Moisy:
Size of Multilayer Networks for Exact Learning: Analytic Approach. NIPS 1996: 162-168
Coauthor Index
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