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Luis de la Ossa
- > Home > Persons > Luis de la Ossa
Publications
- 2019
- [c24]Luis de la Ossa, Pablo Bermejo, Juan A. Aledo, José A. Gámez, José Miguel Puerta, Cristina Romero-González, Jacinto Arias, Javier Cózar, Enrique González Rodrigo, Juan Ignacio Alonso-Barba, Jesus Martínez-Gómez:
CiDAEN: An Online Data Science Course. HELMeTO 2019: 113-124 - 2018
- [j11]Juan Ignacio Alonso-Barba, Luis de la Ossa, José A. Gámez, José Miguel Puerta:
On the use of local search heuristics to improve GES-based Bayesian network learning. Appl. Soft Comput. 64: 366-376 (2018) - [j10]Javier Cózar, Luis delaOssa, José A. Gámez:
Learning compact zero-order TSK fuzzy rule-based systems for high-dimensional problems using an Apriori + local search approach. Inf. Sci. 433-434: 1-16 (2018) - [j9]Javier Cózar, Francesco Marcelloni, José A. Gámez, Luis de la Ossa:
Building efficient fuzzy regression trees for large scale and high dimensional problems. J. Big Data 5: 49 (2018) - 2017
- [c23]Javier Cózar, Luis de la Ossa, José A. Gámez:
Generation of first-order TSK rules based on the apriori + search approach. CEC 2017: 1675-1682 - 2015
- [c22]Juan Ignacio Alonso-Barba, Luis de la Ossa, Olivier Regnier-Coudert, John A. W. McCall, José A. Gámez, José Miguel Puerta:
Ant Colony and Surrogate Tree-Structured Models for Orderings-Based Bayesian Network Learning. GECCO 2015: 543-550 - 2014
- [j7]Javier Cózar, Luis de la Ossa, José A. Gámez:
Learning TSK-0 linguistic fuzzy rules by means of local search algorithms. Appl. Soft Comput. 21: 57-71 (2014) - [c20]Javier Cózar, Luis de la Ossa, José A. Gámez:
TSK-0 Fuzzy Rule-Based Systems for High-Dimensional Problems Using the Apriori Principle for Rule Generation. RSCTC 2014: 270-279 - 2013
- [j6]Juan Ignacio Alonso-Barba, Luis delaOssa, José A. Gámez, José Miguel Puerta:
Scaling up the Greedy Equivalence Search algorithm by constraining the search space of equivalence classes. Int. J. Approx. Reason. 54(4): 429-451 (2013) - 2012
- [j5]Pablo Bermejo, Luis de la Ossa, José A. Gámez, José Miguel Puerta:
Fast wrapper feature subset selection in high-dimensional datasets by means of filter re-ranking. Knowl. Based Syst. 25(1): 35-44 (2012) - [c19]Pablo Bermejo, Luis Redondo, Luis delaOssa, Daniel Rodríguez, M. Julia Flores, Carmen Urea, José A. Gámez, Jesus Martínez-Gómez, José Miguel Puerta:
Evaluation of a Thermal-Comfort Control System Using Real Data. KES 2012: 746-755 - 2011
- [c16]Juan Ignacio Alonso-Barba, Luis de la Ossa, José A. Gámez, José Miguel Puerta:
Scaling Up the Greedy Equivalence Search Algorithm by Constraining the Search Space of Equivalence Classes. ECSQARU 2011: 194-205 - [c15]Pablo Bermejo, Luis de la Ossa, José A. Gámez, José Miguel Puerta:
Enhancing Incremental Feature Subset Selection in High-Dimensional Databases by Adding a Backward Step. ISCIS 2011: 93-97 - [c14]Javier Cózar, Luis delaOssa, José A. Gámez:
Learning heterogeneus cooperative linguistic fuzzy rules using local search: Enhancing the COR search space. ISDA 2011: 475-480 - [c12]Pablo Bermejo, Luis de la Ossa, José A. Gámez, José Miguel Puerta:
A study on different backward feature selection criteria over high-dimensional databases. ISDA 2011: 1300-1305 - 2010
- [c11]Luis delaOssa, José A. Gámez, José Miguel Puerta:
Learning cooperative linguistic fuzzy rules using fast local search algorithms. FUZZ-IEEE 2010: 1-8 - 2009
- [j3]Luis de la Ossa, José A. Gámez, José Miguel Puerta:
Learning weighted linguistic fuzzy rules by using specifically-tailored hybrid estimation of distribution algorithms. Int. J. Approx. Reason. 50(3): 541-560 (2009) - [c9]Luis de la Ossa, José A. Gámez, Juan L. Mateo, José Miguel Puerta:
Avoiding premature convergence in estimation of distribution algorithms. IEEE Congress on Evolutionary Computation 2009: 455-462 - 2008
- [c7]Luis delaOssa, José A. Gámez, Verónica López:
Improvement of a car racing controller by means of Ant Colony Optimization algorithms. CIG 2008: 365-371 - 2007
- [j2]Luis de la Ossa, M. Julia Flores, José A. Gámez, Juan L. Mateo, José Miguel Puerta:
Initial breeding value prediction on Manchego sheep by using rule-based systems. Expert Syst. Appl. 33(1): 96-109 (2007) - 2006
- [j1]Luis de la Ossa, José A. Gámez, José Miguel Puerta:
Initial approaches to the application of islands-based parallel EDAs in continuous domains. J. Parallel Distributed Comput. 66(8): 991-1001 (2006) - [c6]Luis delaOssa, José A. Gámez, José Miguel Puerta:
Learning weighted linguistic fuzzy rules with estimation of distribution algorithms. IEEE Congress on Evolutionary Computation 2006: 900-907 - [c5]Luis de la Ossa, José A. Gámez, José Miguel Puerta:
Improvement in the Performance of Island Based Genetic Algorithms Through Path Relinking. Hybrid Metaheuristics 2006: 42-56 - 2005
- [c4]Luis de la Ossa, José A. Gámez, José Miguel Puerta:
Improving model combination through local search in parallel univariate EDAs. Congress on Evolutionary Computation 2005: 1426-1433 - [c3]Luis de la Ossa, José A. Gámez, José Miguel Puerta:
Initial Approaches to the Application of Islands-Based Parallel EDAs in Continuous Domains. ICPP Workshops 2005: 580-587 - 2004
- [c2]Luis de la Ossa, José A. Gámez, José Miguel Puerta:
Migration of Probability Models Instead of Individuals: An Alternative When Applying the Island Model to EDAs. PPSN 2004: 242-252 - 2003
- [c1]Luis de la Ossa, José A. Gámez, José Miguel Puerta:
Heuristic Based Sampling in Estimation of Distribution Algorithms: An Initial Approach. CAEPIA 2003: 384-393
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