Inés María Galván

	2011
34		Sandra García, David Quintana, Inés María Galván, Pedro Isasi: Portfolio Optimization Using SPEA2 with Resampling. IDEAL 2011: 127-134
33		Inés María Galván, Jos M. Valls, Miguel García, Pedro Isasi: A lazy learning approach for building classification models. Int. J. Intell. Syst. 26(8): 773-786 (2011)
32		Esteban García-Cuesta, Inés María Galván, Antonio J. de Castro: Recursive Discriminant Regression Analysis to Find Homogeneous Groups. Int. J. Neural Syst. 21(1): 95-101 (2011)
	2010
31		Sandra García, Ricardo Aler, Inés María Galván: Using Evolutionary Multiobjective Techniques for Imbalanced Classification Data. ICANN (1) 2010: 422-427
30		Ricardo Aler, Inés María Galván, José María Valls: Evolving spatial and frequency selection filters for Brain-Computer Interfaces. IEEE Congress on Evolutionary Computation 2010: 1-7
	2009
29		Inés María Galván, José María Valls, Nicolas Lecomte, Pedro Isasi: A Lazy Approach for Machine Learning Algorithms. AIAI 2009: 517-522
28		Ricardo Aler, Inés María Galván, José María Valls: Improving Classification for Brain Computer Interfaces using Transitions and a Moving Window. BIOSIGNALS 2009: 65-71
27		Carlos Segura, Alejandro Cervantes, Antonio J. Nebro, María Dolores Jaraíz-Simón, Eduardo Segredo, Sandra García, Francisco Luna, Juan Antonio Gómez Pulido, Gara Miranda, Cristóbal Luque, Enrique Alba, Miguel Ángel Vega Rodríguez, Coromoto León, Inés María Galván: Optimizing the DFCN Broadcast Protocol with a Parallel Cooperative Strategy of Multi-Objective Evolutionary Algorithms. EMO 2009: 305-319
26		Esteban García-Cuesta, Inés María Galván, Antonio J. de Castro: Discriminant Regression Analysis to Find Homogeneous Structures. IDEAL 2009: 191-199
25		Sandra García, Cristóbal Luque, Alejandro Cervantes, Inés María Galván: Multiobjective Algorithms Hybridization to Optimize Broadcasting Parameters in Mobile Ad-Hoc Networks. IWANN (1) 2009: 728-735
24		Esteban García-Cuesta, Inés María Galván, Antonio J. de Castro: Supervised clustering via principal component analysis in a retrieval application. KDD Workshop on Knowledge Discovery from Sensor Data 2009: 97-104
23		Alejandro Cervantes, Inés María Galván, Pedro Isasi: AMPSO: A New Particle Swarm Method for Nearest Neighborhood Classification. IEEE Transactions on Systems, Man, and Cybernetics, Part B 39(5): 1082-1091 (2009)
22		Alejandro Cervantes, Inés María Galván, Pedro Isasi Viñuela: Michigan Particle Swarm Optimization for Prototype Reduction in Classification Problems. New Generation Comput. 27(3): 239-257 (2009)
	2008
21		Esteban García-Cuesta, Inés María Galván, Antonio J. de Castro: Multilayer perceptron as inverse model in a ground-based remote sensing temperature retrieval problem. Eng. Appl. of AI 21(1): 26-34 (2008)
	2007
20		Alejandro Cervantes, Inés María Galván, Pedro Isasi: An Adaptive Michigan Approach PSO for Nearest Prototype Classification. IWINAC (2) 2007: 287-296
19		José María Valls, Inés María Galván, Pedro Isasi: LRBNN: A Lazy Radial Basis Neural Network model. AI Commun. 20(2): 71-86 (2007)
	2006
18		José María Valls, Inés María Galván, Pedro Isasi: Lazy Training of Radial Basis Neural Networks. ICANN (1) 2006: 198-207
17		Esteban García-Cuesta, Inés María Galván, Antonio J. de Castro: Spectral High Resolution Feature Selection for Retrieval of Combustion Temperature Profiles. IDEAL 2006: 754-762
16		José María Valls, Inés María Galván, Pedro Isasi Viñuela: Improving the Generalization Ability of RBNN Using a Selective Strategy Based on the Gaussian Kernel Function. Computers and Artificial Intelligence 25(1): 1-15 (2006)
	2005
15		Esteban García-Cuesta, Inés María Galván, Antonio J. de Castro: Neural Networks and Spectral Feature Selection for Retrieval of Hot Gases Temperature Profiles. CIMCA/IAWTIC 2005: 81-86
14		Alejandro Cervantes, Inés María Galván, Pedro Isasi: A comparison between the Pittsburgh and Michigan approaches for the binary PSO algorithm. Congress on Evolutionary Computation 2005: 290-297
13		César Estébanez, José María Valls, Ricardo Aler, Inés María Galván: A First Attempt at Constructing Genetic Programming Expressions for EEG Classification. ICANN (1) 2005: 665-670
12		Germán Gutiérrez, Araceli Sanchís, Pedro Isasi Viñuela, José M. Molina, Inés María Galván: Non-Direct Encoding Method Based on Cellular Automata to Design Neural Network Architectures. Computers and Artificial Intelligence 24(3): 225-247 (2005)
	2004
11		José María Valls, Inés María Galván, Pedro Isasi: Lazy Learning in Radial Basis Neural Networks: A Way of Achieving More Accurate Models. Neural Processing Letters 20(2): 105-124 (2004)
	2003
10		José María Valls, Inés María Galván, Pedro Isasi: How the Selection of Training Patterns can Improve the Generalization Capability in Radial Basis Neural Networks. Applied Informatics 2003: 275-280
9		Juan Manuel Alonso-Weber, Inés María Galván, Araceli Sanchis de Miguel: Modified Self-organizing Maps for Line Extraction in Digitized Text Documents. Applied Informatics 2003: 281-286
8		Pedro Isasi, José María Valls, Inés María Galván: A Better Selection of Patterns in Lazy Learning Radial Basis Neural Networks. IWANN (1) 2003: 278-285
	2002
7		Germán Gutiérrez, Inés María Galván, José M. Molina, Araceli Sanchís: Generative Capacities of Cellular Automata Codification for Evolution of NN Codification. ICANN 2002: 314-322
	2001
6		José María Valls, Pedro Isasi, Inés María Galván: Deferring the Learning for Better Generalization in Radial Basis Neural Networks. ICANN 2001: 189-195
5		Germán Gutiérrez, Pedro Isasi, José M. Molina, Araceli Sanchís, Inés María Galván: Evolutionary Cellular Configurations for Designing Feed-Forward Neural Networks Architectures. IWANN (1) 2001: 514-521
4		José M. Molina, Inés María Galván, José María Valls, Andrés Leal: Optimizing the Number of Learning Cycles in the Design of Radial Basis Neural Networks Using a Multi-Agent System. Computers and Artificial Intelligence 20(5): (2001)
3		Inés María Galván, Pedro Isasi, Ricardo Aler, José María Valls: A Selective Learning Method to Improve the Generalization of Multilayer Feedforward Neural Networks. Int. J. Neural Syst. 11(2): 167-177 (2001)
2		Inés María Galván, Pedro Isasi: Multi-step Learning Rule for Recurrent Neural Models: An Application to Time Series Forecasting. Neural Processing Letters 13(2): 115-133 (2001)
	2000
1		José María Valls, José M. Molina, Inés María Galván: Sistema Multiagente para el diseño de Redes de Neuronas de Base Radial Óptimas. Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial 4(10): 18-25 (2000)

Coauthor Index

1	Enrique Alba (Enrique Alba Torres)	[27]
2	Ricardo Aler	[3] [13] [28] [30] [31]
3	Juan Manuel Alonso-Weber	[9]
4	Cristóbal Luque del Arco-Calderón (Cristóbal Luque)	[25] [27]
5	Antonio J. de Castro	[15] [17] [21] [24] [26] [32]
6	Alejandro Cervantes	[14] [20] [22] [23] [25] [27]
7	César Estébanez	[13]
8	Miguel García	[33]
9	Sandra García	[25] [27] [31] [34]
10	Esteban García-Cuesta	[15] [17] [21] [24] [26] [32]
11	Germán Gutiérrez (Germán Gutiérrez Sánchez)	[5] [7] [12]
12	María Dolores Jaraíz-Simón	[27]
13	Andrés Leal	[4]
14	Nicolas Lecomte	[29]
15	Coromoto León	[27]
16	José M. Molina López (José Manuel Molina, José M. Molina)	[1] [4] [5] [7] [12]
17	Francisco Luna	[27]
18	Gara Miranda (Gara Miranda-Valladares)	[27]
19	Antonio J. Nebro (Antonio José Nebro)	[27]
20	Juan Antonio Gómez Pulido	[27]
21	David Quintana	[34]
22	Araceli Sanchís (Araceli Sanchis de Miguel)	[5] [7] [9] [12]
23	Eduardo Segredo	[27]
24	Carlos Segura	[27]
25	Jos M. Valls	[33]
26	José María Valls	[1] [3] [4] [6] [8] [10] [11] [13] [16] [18] [19] [28] [29] [30]
27	Miguel A. Vega-Rodríguez (Miguel Ángel Vega Rodríguez)	[27]
28	Pedro Isasi Viñuela (Pedro Isasi)	[2] [3] [5] [6] [8] [10] [11] [12] [14] [16] [18] [19] [20] [22] [23] [29] [33] [34]

Colors in the list of coauthors

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