Folgen
Jose M. Peña
Jose M. Peña
Bestätigte E-Mail-Adresse bei liu.se - Startseite
Titel
Zitiert von
Zitiert von
Jahr
An empirical comparison of four initialization methods for the k-means algorithm
JM Pena, JA Lozano, P Larranaga
Pattern recognition letters 20 (10), 1027-1040, 1999
11271999
Optimization in continuous domains by learning and simulation of Gaussian networks
P Larrañaga, R Etxeberria, JA Lozano, JM Peña
2802000
Towards scalable and data efficient learning of Markov boundaries
JM Pena, R Nilsson, J Björkegren, J Tegnér
International Journal of Approximate Reasoning 45 (2), 211-232, 2007
2402007
Optimization by learning and simulation of Bayesian and Gaussian networks
P Larranaga
1999 EHU-KZAAIK-4/99, University of the Basque Country, 1999
2331999
Consistent feature selection for pattern recognition in polynomial time
R Nilsson, JM Pena, J Björkegren, J Tegnér
The Journal of Machine Learning Research 8, 589-612, 2007
2022007
Combinatorial optimization by learning and simulation of Bayesian networks
P Larranaga, R Etxeberria, JA Lozano, JM Pena
arXiv preprint arXiv:1301.3871, 2013
1712013
Growing Bayesian network models of gene networks from seed genes
JM Pena, J Björkegren, J Tegnér
Bioinformatics 21 (suppl_2), ii224-ii229, 2005
912005
Dimensionality reduction in unsupervised learning of conditional Gaussian networks
JM Pena, JA Lozano, P Larranaga, I Inza
IEEE Transactions on Pattern Analysis and Machine Intelligence 23 (6), 590-603, 2001
802001
An improved Bayesian structural EM algorithm for learning Bayesian networks for clustering
JM Peña, JA Lozano, P Larrañaga
Pattern Recognition Letters 21 (8), 779-786, 2000
762000
Learning recursive Bayesian multinets for data clustering by means of constructive induction
JM Peña, JA Lozano, P Larrañaga
Machine Learning 47, 63-89, 2002
672002
On local optima in learning Bayesian networks
JD Nielsen, T Kocka, JM Pena
arXiv preprint arXiv:1212.2500, 2012
652012
Unsupervised feature subset selection
N Søndberg-Madsen, C Thomsen, JM Pena
Aalborg University. Department of Computer Science, 2003
612003
Globally multimodal problem optimization via an estimation of distribution algorithm based on unsupervised learning of Bayesian networks
JM Peña, JA Lozano, P Larrañaga
Evolutionary Computation 13 (1), 43-66, 2005
522005
Learning gaussian graphical models of gene networks with false discovery rate control
JM Pena
Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics …, 2008
442008
Learning dynamic Bayesian network models via cross-validation
JM Pena, J Björkegren, J Tegnér
Pattern Recognition Letters 26 (14), 2295-2308, 2005
442005
Evaluating feature selection for SVMs in high dimensions
R Nilsson, JM Pena, J Björkegren, J Tegnér
Machine Learning: ECML 2006: 17th European Conference on Machine Learning …, 2006
402006
Scalable, efficient and correct learning of Markov boundaries under the faithfulness assumption
JM Pena, J Björkegren, J Tegnér
Symbolic and Quantitative Approaches to Reasoning with Uncertainty: 8th …, 2005
402005
Unsupervised learning of Bayesian networks via estimation of distribution algorithms: an application to gene expression data clustering
JM Pena, JA Lozano, P Larranaga
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems …, 2004
362004
Detecting multivariate differentially expressed genes
R Nilsson, JM Peña, J Björkegren, J Tegnér
BMC bioinformatics 8 (1), 1-10, 2007
352007
Finding consensus Bayesian network structures
JM Pena
Journal of Artificial Intelligence Research 42, 661-687, 2011
302011
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20