Mario Marchand

	2012
32		Mohak Shah, Mario Marchand, Jacques Corbeil: Feature Selection with Conjunctions of Decision Stumps and Learning from Microarray Data. IEEE Trans. Pattern Anal. Mach. Intell. 34(1): 174-186 (2012)
31		Alexandre Lacoste, François Laviolette, Mario Marchand: Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets. Journal of Machine Learning Research - Proceedings Track 22: 665-675 (2012)
	2011
30		Pascal Germain, Alexandre Lacoste, François Laviolette, Mario Marchand, Sara Shanian: A PAC-Bayes Sample-compression Approach to Kernel Methods. ICML 2011: 297-304
29		Jean-Francis Roy, François Laviolette, Mario Marchand: From PAC-Bayes Bounds to Quadratic Programs for Majority Votes. ICML 2011: 649-656
	2010
28		Alexandre Lacasse, François Laviolette, Mario Marchand, Francis Turgeon-Boutin: Learning with Randomized Majority Votes. ECML/PKDD (2) 2010: 162-177
27		Mohak Shah, Mario Marchand, Jacques Corbeil: Feature Selection with Conjunctions of Decision Stumps and Learning from Microarray Data CoRR abs/1005.0530: (2010)
26		François Laviolette, Mario Marchand, Mohak Shah, Sara Shanian: Learning the set covering machine by bound minimization and margin-sparsity trade-off. Machine Learning 78(1-2): 175-201 (2010)
	2009
25		Pascal Germain, Alexandre Lacasse, François Laviolette, Mario Marchand: PAC-Bayesian learning of linear classifiers. ICML 2009: 45
24		Pascal Germain, Alexandre Lacasse, François Laviolette, Mario Marchand, Sara Shanian: From PAC-Bayes Bounds to KL Regularization. NIPS 2009: 603-610
	2008
23		François Laviolette, Mario Marchand, Sara Shanian: Selective Sampling for Classification. Canadian Conference on AI 2008: 191-202
	2007
22		François Laviolette, Mario Marchand: PAC-Bayes Risk Bounds for Stochastic Averages and Majority Votes of Sample-Compressed Classifiers. Journal of Machine Learning Research 8: 1461-1487 (2007)
21		Zakria Hussain, François Laviolette, Mario Marchand, John Shawe-Taylor, S. Charles Brubaker, Matthew D. Mullin: Revised Loss Bounds for the Set Covering Machine and Sample-Compression Loss Bounds for Imbalanced Data. Journal of Machine Learning Research 8: 2533-2549 (2007)
	2006
20		Luc Lamontagne, Mario Marchand: Advances in Artificial Intelligence, 19th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2006, Québec City, Québec, Canada, June 7-9, 2006, Proceedings Springer 2006
19		Pascal Germain, Alexandre Lacasse, François Laviolette, Mario Marchand: A PAC-Bayes Risk Bound for General Loss Functions. NIPS 2006: 449-456
18		Alexandre Lacasse, François Laviolette, Mario Marchand, Pascal Germain, Nicolas Usunier: PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier. NIPS 2006: 769-776
	2005
17		François Laviolette, Mario Marchand, Mohak Shah: Margin-Sparsity Trade-Off for the Set Covering Machine. ECML 2005: 206-217
16		François Laviolette, Mario Marchand: PAC-Bayes risk bounds for sample-compressed Gibbs classifiers. ICML 2005: 481-488
15		François Laviolette, Mario Marchand, Mohak Shah: A PAC-Bayes approach to the Set Covering Machine. NIPS 2005
14		Mario Marchand, Marina Sokolova: Learning with Decision Lists of Data-Dependent Features. Journal of Machine Learning Research 6: 427-451 (2005)
	2004
13		Mario Marchand, Mohak Shah: PAC-Bayes Learning of Conjunctions and Classification of Gene-Expression Data. NIPS 2004
	2003
12		Mario Marchand, Mohak Shah, John Shawe-Taylor, Marina Sokolova: The Set Covering Machine with Data-Dependent Half-Spaces. ICML 2003: 520-527
	2002
11		Marina Sokolova, Mario Marchand, Nathalie Japkowicz, John Shawe-Taylor: The Decision List Machine. NIPS 2002: 921-928
10		Mario Marchand, John Shawe-Taylor: The Set Covering Machine. Journal of Machine Learning Research 3: 723-746 (2002)
	2001
9		Mario Marchand, John Shawe-Taylor: Learning with the Set Covering Machine. ICML 2001: 345-352
	1996
8		Mostefa Golea, Mario Marchand, Thomas R. Hancock: On learning ?-perceptron networks on the uniform distribution. Neural Networks 9(1): 67-82 (1996)
	1995
7		Mario Marchand, Saeed Hadjifaradji: Strong Unimodality and Exact Learning of Constant Depth µ-Perceptron Networks. NIPS 1995: 288-294
	1994
6		Mario Marchand, Saeed Hadjifaradji: Learning Stochastic Perceptrons Under k-Blocking Distributions. NIPS 1994: 279-286
5		Thomas R. Hancock, Mostefa Golea, Mario Marchand: Learning Nonoverlapping Perceptron Networks from Examples and Membership Queries. Machine Learning 16(3): 161-183 (1994)
	1993
4		Mostefa Golea, Mario Marchand: Average Case Analysis of the Clipped Hebb Rule for Nonoverlapping Perception Networks. COLT 1993: 151-157
3		Mostefa Golea, Mario Marchand: Polynomial Time Algorithms for Learning Neural Nets of NonoverlappingPerceptrons. Computational Intelligence 9: 155-170 (1993)
2		Mostefa Golea, Mario Marchand: On Learning Perceptrons with Binary Weights. Neural Computation 5(5): 767-782 (1993)
	1992
1		Mostefa Golea, Mario Marchand, Thomas R. Hancock: On Learning µ-Perceptron Networks with Binary Weights. NIPS 1992: 591-598

Coauthor Index

1	S. Charles Brubaker	[21]
2	Jacques Corbeil	[27] [32]
3	Pascal Germain	[18] [19] [24] [25] [30]
4	Mostefa Golea	[1] [2] [3] [4] [5] [8]
5	Saeed Hadjifaradji	[6] [7]
6	Thomas R. Hancock	[1] [5] [8]
7	Zakria Hussain	[21]
8	Nathalie Japkowicz	[11]
9	Alexandre Lacasse	[18] [19] [24] [25] [28]
10	Alexandre Lacoste	[30] [31]
11	Luc Lamontagne	[20]
12	François Laviolette	[15] [16] [17] [18] [19] [21] [22] [23] [24] [25] [26] [28] [29] [30] [31]
13	Matthew D. Mullin	[21]
14	Jean-Francis Roy	[29]
15	Mohak Shah	[12] [13] [15] [17] [26] [27] [32]
16	Sara Shanian	[23] [24] [26] [30]
17	John Shawe-Taylor	[9] [10] [11] [12] [21]
18	Marina Sokolova	[11] [12] [14]
19	Francis Turgeon-Boutin	[28]
20	Nicolas Usunier	[18]

Colors in the list of coauthors

Last update Sun Jun 3 16:06:10 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page