André Elisseeff

	2010
29		Giuseppe Paleologo, André Elisseeff, Gianluca Antonini: Subagging for credit scoring models. European Journal of Operational Research 201(2): 490-499 (2010)
28		André Elisseeff, Jean-Philippe Pellet, Eleni Pratsini: Causal networks for risk and compliance: Methodology and application. IBM Journal of Research and Development 54(3): 6 (2010)
	2008
27		Jean-Philippe Pellet, André Elisseeff: Finding Latent Causes in Causal Networks: an Efficient Approach Based on Markov Blankets. NIPS 2008: 1249-1256
26		Ulf H. Nielsen, Jean-Philippe Pellet, André Elisseeff: Explanation Trees for Causal Bayesian Networks. UAI 2008: 427-434
25		Jean-Philippe Pellet, André Elisseeff: Using Markov Blankets for Causal Structure Learning. Journal of Machine Learning Research 9: 1295-1342 (2008)
24		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. Journal of Machine Learning Research - Proceedings Track 3: 1-33 (2008)
	2007
23		Jean-Philippe Pellet, André Elisseeff: A Partial Correlation-Based Algorithm for Causal Structure Discovery with Continuous Variables. IDA 2007: 229-239
22		Olivier Bousquet, André Elisseeff: Guest editorial: Learning theory. Machine Learning 66(2-3): 115-118 (2007)
	2005
21		Giuliano Tirenni, Abderrahim Labbi, André Elisseeff, Cesar Berrospi: Efficient Allocation of Marketing Resources using Dynamic Programming. SDM 2005
20		Jason Weston, Christina S. Leslie, Eugene Ie, Dengyong Zhou, André Elisseeff, William Stafford Noble: Semi-supervised protein classification using cluster kernels. Bioinformatics 21(15): 3241-3247 (2005)
19		André Elisseeff, Theodoros Evgeniou, Massimiliano Pontil: Stability of Randomized Learning Algorithms. Journal of Machine Learning Research 6: 55-79 (2005)
	2004
18		Theodoros Evgeniou, Massimiliano Pontil, André Elisseeff: Leave One Out Error, Stability, and Generalization of Voting Combinations of Classifiers. Machine Learning 55(1): 71-97 (2004)
17		Yann Guermeur, Gianluca Pollastri, André Elisseeff, Dominique Zelus, Hélène Paugam-Moisy, Pierre Baldi: Combining protein secondary structure prediction models with ensemble methods of optimal complexity. Neurocomputing 56: 305-327 (2004)
	2003
16		Jason Weston, Christina S. Leslie, Dengyong Zhou, André Elisseeff, William Stafford Noble: Semi-supervised Protein Classification Using Cluster Kernels. NIPS 2003
15		Jason Weston, Fernando Pérez-Cruz, Olivier Bousquet, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf: Feature selection and transduction for prediction of molecular bioactivity for drug design. Bioinformatics 19(6): 764-771 (2003)
14		Isabelle Guyon, André Elisseeff: An Introduction to Variable and Feature Selection. Journal of Machine Learning Research 3: 1157-1182 (2003)
13		Jason Weston, André Elisseeff, Bernhard Schölkopf, Michael E. Tipping: Use of the Zero-Norm with Linear Models and Kernel Methods. Journal of Machine Learning Research 3: 1439-1461 (2003)
	2002
12		Savina Andonova, André Elisseeff, Theodoros Evgeniou, Massimiliano Pontil: A Simple Algorithm for Learning Stable Machines. ECAI 2002: 513-517
11		Jason Weston, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf, Vladimir Vapnik: Kernel Dependency Estimation. NIPS 2002: 873-880
10		Asa Ben-Hur, André Elisseeff, Isabelle Guyon: A Stability Based Method for Discovering Structure in Clustered Data. Pacific Symposium on Biocomputing 2002: 6-17
9		Olivier Bousquet, André Elisseeff: Stability and Generalization. Journal of Machine Learning Research 2: 499-526 (2002)
8		Olivier Bousquet, André Elisseeff: Stability and Generalization. Journal of Machine Learning Research 2: 499-526 (2002)
	2001
7		Nello Cristianini, John Shawe-Taylor, André Elisseeff, Jaz S. Kandola: On Kernel-Target Alignment. NIPS 2001: 367-373
6		André Elisseeff, Jason Weston: A kernel method for multi-labelled classification. NIPS 2001: 681-687
	2000
5		Hélène Paugam-Moisy, André Elisseeff, Yann Guermeur: Generalization Performance of Multiclass Discriminant Models. IJCNN (4) 2000: 177-182
4		Yann Guermeur, André Elisseeff, Hélène Paugam-Moisy: A New Multi-Class SVM Based on a Uniform Convergence Result. IJCNN (4) 2000: 183-188
3		Olivier Bousquet, André Elisseeff: Algorithmic Stability and Generalization Performance. NIPS 2000: 196-202
	1999
2		André Elisseeff, Hélène Paugam-Moisy: JNN, a randomized algorithm for training multilayer networks in polynomial time. Neurocomputing 29(1-3): 3-24 (1999)
	1996
1		André Elisseeff, Hélène Paugam-Moisy: Size of Multilayer Networks for Exact Learning: Analytic Approach. NIPS 1996: 162-168

Coauthor Index

1	Constantin F. Aliferis	[24]
2	Savina Andonova	[12]
3	Gianluca Antonini	[29]
4	Pierre Baldi	[17]
5	Asa Ben-Hur	[10]
6	Cesar Berrospi	[21]
7	Olivier Bousquet	[3] [8] [9] [15] [22]
8	Olivier Chapelle	[11] [15]
9	Gregory F. Cooper	[24]
10	Nello Cristianini	[7]
11	Theodoros Evgeniou	[12] [18] [19]
12	Yann Guermeur	[4] [5] [17]
13	Isabelle Guyon	[10] [14] [24]
14	Eugene Ie	[20]
15	Jaz S. Kandola	[7]
16	Abderrahim Labbi	[21]
17	Christina S. Leslie	[16] [20]
18	Ulf H. Nielsen	[26]
19	William Stafford Noble	[16] [20]
20	Giuseppe Paleologo	[29]
21	Hélène Paugam-Moisy	[1] [2] [4] [5] [17]
22	Jean-Philippe Pellet	[23] [24] [25] [26] [27] [28]
23	Fernando Pérez-Cruz	[15]
24	Gianluca Pollastri	[17]
25	Massimiliano Pontil	[12] [18] [19]
26	Eleni Pratsini	[28]
27	Bernhard Schölkopf	[11] [13] [15]
28	John Shawe-Taylor	[7]
29	Peter Spirtes	[24]
30	Alexander R. Statnikov	[24]
31	Michael E. Tipping	[13]
32	Giuliano Tirenni	[21]
33	Vladimir Vapnik	[11]
34	Jason Weston	[6] [11] [13] [15] [16] [20]
35	Dominique Zelus	[17]
36	Dengyong Zhou	[16] [20]

Colors in the list of coauthors

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