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22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2014 - Proceedings(2)
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23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2015 - Proceedings(1)
Advances in Intelligent Systems and Computing(1)
ICPRAM 2014 - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods(1)
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scopus(8)
Advances in computational intelligence and learning (ESANN 2009)
OtherAbstract:Palabras claves:Autores:Cecilio Angulo Bahón, Lee J.A., Schleif F.Fuentes:scopusGeneralized kernel framework for unsupervised spectral methods of dimensionality reduction
Conference ObjectAbstract: This work introduces a generalized kernel perspective for spectral dimensionality reduction approachPalabras claves:Autores:Diego Hernán Peluffo-Ordóñez, Lee J.A., Verleysen M.Fuentes:scopusGeometrical homotopy for data visualization
Conference ObjectAbstract: This work presents an approach allowing for an interactive visualization of dimensionality reductionPalabras claves:Autores:Alvarado-PÉrez J.C., Diego Hernán Peluffo-Ordóñez, Lee J.A., Verleysen M.Fuentes:scopusMulti-scale similarities in stochastic neighbour embedding: Reducing dimensionality while preserving both local and global structure
ArticleAbstract: Stochastic neighbour embedding (SNE) and its variants are methods of nonlinear dimensionality reductPalabras claves:Data visualisation, Jensen-Shannon divergence, Manifold learning, Nonlinear dimensionality reduction, Stochastic neighbour embeddingAutores:Diego Hernán Peluffo-Ordóñez, Lee J.A., Verleysen M.Fuentes:scopusMultiscale stochastic neighbor embedding: Towards parameter-free dimensionality reduction
Conference ObjectAbstract: Stochastic neighbor embedding (SNE) is a method of dimensionality reduction that involves softmax siPalabras claves:Autores:Diego Hernán Peluffo-Ordóñez, Lee J.A., Verleysen M.Fuentes:scopusUnsupervised relevance analysis for feature extraction and selection: A distance-based approach for feature relevance
Conference ObjectAbstract: The aim of this paper is to propose a new generalized formulation for feature extraction based on diPalabras claves:Feature Extraction, Feature relevance, feature selection, M-norm, PCaAutores:Castellanos-Dominguez G., Diego Hernán Peluffo-Ordóñez, Lee J.A., Rodríguez J.L., Verleysen M.Fuentes:scopusShort Review of Dimensionality Reduction Methods Based on Stochastic Neighbour Embedding
Conference ObjectAbstract: Dimensionality reduction methods aimed at preserving the data topology have shown to be suitable forPalabras claves:Dimensionality reduction, divergences, similarity, stochastic neighbor embeddingAutores:Diego Hernán Peluffo-Ordóñez, Lee J.A., Verleysen M.Fuentes:scopusRecent methods for dimensionality reduction: A brief comparative analysis
Conference ObjectAbstract: Dimensionality reduction is a key stage for both the design of a pattern recognition system or dataPalabras claves:Autores:Diego Hernán Peluffo-Ordóñez, Lee J.A., Verleysen M.Fuentes:scopus