2008 |
28 | EE | Antonio LaTorre,
José Manuel Peña,
Víctor Robles,
Santiago Muelas:
Using multiple offspring sampling to guide genetic algorithms to solve permutation problems.
GECCO 2008: 1119-1120 |
27 | EE | Santiago Muelas,
José Manuel Peña,
Víctor Robles,
Antonio LaTorre:
Voronoi-initializated island models for solving real-coded deceptive problems.
GECCO 2008: 993-1000 |
26 | EE | Santiago Muelas,
José Manuel Peña,
Víctor Robles,
A. La Torre,
P. de Miguel:
Machine Learning to Analyze Migration Parameters in Parallel Genetic Algorithms.
Innovations in Hybrid Intelligent Systems 2008: 199-206 |
2007 |
25 | EE | María S. Pérez,
Alberto Sánchez,
Víctor Robles,
Pilar Herrero,
José Manuel Peña:
Design and implementation of a data mining grid-aware architecture.
Future Generation Comp. Syst. 23(1): 42-47 (2007) |
2006 |
24 | EE | María S. Pérez,
Jesús Carretero,
Félix García Carballeira,
José Manuel Peña,
Víctor Robles:
MAPFS: A flexible multiagent parallel file system for clusters.
Future Generation Comp. Syst. 22(5): 620-632 (2006) |
2005 |
23 | EE | María S. Pérez,
Alberto Sánchez,
Pilar Herrero,
Víctor Robles,
José Manuel Peña:
Adapting the Weka Data Mining Toolkit to a Grid Based Environment.
AWIC 2005: 492-497 |
22 | EE | José Manuel Peña,
José Antonio Lozano,
Pedro Larrañaga:
Globally Multimodal Problem Optimization Via an Estimation of Distribution Algorithm Based on Unsupervised Learning of Bayesian Networks.
Evolutionary Computation 13(1): 43-66 (2005) |
21 | EE | María S. Pérez,
Alberto Sánchez,
José Manuel Peña,
Víctor Robles:
A new formalism for dynamic reconfiguration of data servers in a cluster.
J. Parallel Distrib. Comput. 65(10): 1134-1145 (2005) |
20 | EE | Pedro Larrañaga,
José Antonio Lozano,
José Manuel Peña,
Iñaki Inza:
Editorial.
Machine Learning 59(3): 211-212 (2005) |
2004 |
19 | EE | José Manuel Peña,
Víctor Robles,
Oscar Marbán,
María S. Pérez:
Bayesian Methods to Estimate Future Load in Web Farms.
AWIC 2004: 217-226 |
18 | EE | María S. Pérez,
Alberto Sánchez,
Víctor Robles,
José Manuel Peña,
Jemal H. Abawajy:
Cooperation model of a multiagent parallel file system for clusters.
CCGRID 2004: 595-601 |
17 | | María S. Pérez,
Alberto Sánchez,
José Manuel Peña,
Víctor Robles,
Jesús Carretero,
Félix García:
Storage groups: A new approach for providing dynamic reconfiguration in data-based clusters.
Parallel and Distributed Computing and Networks 2004: 70-75 |
16 | EE | Alberto Sánchez,
María S. Pérez,
Víctor Robles,
José Manuel Peña,
Pilar Herrero:
A Flexible Two-Level I/O Architecture for Grids.
SAG 2004: 50-58 |
15 | EE | Víctor Robles,
Pedro Larrañaga,
José Manuel Peña,
Ernestina Menasalvas Ruiz,
María S. Pérez,
Vanessa Herves,
Anita Wasilewska:
Bayesian network multi-classifiers for protein secondary structure prediction.
Artificial Intelligence in Medicine 31(2): 117-136 (2004) |
14 | EE | Ernestina Menasalvas Ruiz,
Socorro Millán,
José Manuel Peña,
Michael Hadjimichael,
Oscar Marbán:
Subsessions: A granular approach to click path analysis.
Int. J. Intell. Syst. 19(7): 619-637 (2004) |
13 | EE | José Manuel Peña,
José Antonio Lozano,
Pedro Larrañaga:
Unsupervised Learning Of Bayesian Networks Via Estimation Of Distribution Algorithms: An Application To Gene Expression Data Clustering.
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 12(Supplement-1): 63-82 (2004) |
2003 |
12 | | Jens D. Nielsen,
Tomás Kocka,
José Manuel Peña:
On Local Optima in Learning Bayesian Networks.
UAI 2003: 435-442 |
2002 |
11 | EE | José Manuel Peña,
José Antonio Lozano,
Pedro Larrañaga:
Unsupervised Learning of Bayesian Networks Via Estimation of Distribution Algorithms.
Probabilistic Graphical Models 2002 |
10 | | José Manuel Peña,
José Antonio Lozano,
Pedro Larrañaga:
Learning Recursive Bayesian Multinets for Data Clustering by Means of Constructive Induction.
Machine Learning 47(1): 63-89 (2002) |
2001 |
9 | EE | José Manuel Peña,
José Antonio Lozano,
Pedro Larrañaga,
Iñaki Inza:
Dimensionality Reduction in Unsupervised Learning of Conditional Gaussian Networks.
IEEE Trans. Pattern Anal. Mach. Intell. 23(6): 590-603 (2001) |
8 | EE | José Manuel Peña,
José Antonio Lozano,
Pedro Larrañaga:
Performance evaluation of compromise conditional Gaussian networks for data clustering.
Int. J. Approx. Reasoning 28(1): 23-50 (2001) |
2000 |
7 | EE | José Manuel Peña,
Fazel Famili,
Sylvain Létourneau:
Data mining to detect abnormal behavior in aerospace data.
KDD 2000: 390-397 |
6 | EE | Pedro Larrañaga,
Ramon Etxeberria,
José Antonio Lozano,
José Manuel Peña:
Combinatonal Optimization by Learning and Simulation of Bayesian Networks.
UAI 2000: 343-352 |
5 | EE | José Manuel Peña,
José Antonio Lozano,
Pedro Larrañaga:
An improved Bayesian structural EM algorithm for learning Bayesian networks for clustering.
Pattern Recognition Letters 21(8): 779-786 (2000) |
1999 |
4 | EE | José Manuel Peña,
Sylvain Létourneau,
Fazel Famili:
Application of Rough Sets Algorithms to Prediction of Aircraft Component Failure.
IDA 1999: 473-486 |
3 | EE | José Manuel Peña,
José Antonio Lozano,
Pedro Larrañaga:
An empirical comparison of four initialization methods for the K-Means algorithm.
Pattern Recognition Letters 20(10): 1027-1040 (1999) |
2 | EE | Iñaki Inza,
Pedro Larrañaga,
Basilio Sierra,
Ramon Etxeberria,
José Antonio Lozano,
José Manuel Peña:
Representing the behaviour of supervised classification learning algorithms by Bayesian networks.
Pattern Recognition Letters 20(11-13): 1201-1209 (1999) |
1 | EE | José Manuel Peña,
José Antonio Lozano,
Pedro Larrañaga:
Learning Bayesian networks for clustering by means of constructive induction.
Pattern Recognition Letters 20(11-13): 1219-1230 (1999) |