Mostrando 7 resultados de: 7
Publisher
22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2014 - Proceedings(2)
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)
IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - CIDM 2014: 2014 IEEE Symposium on Computational Intelligence and Data Mining, Proceedings(1)
Área temáticas
Métodos informáticos especiales(4)
Funcionamiento de bibliotecas y archivos(3)
Ciencias de la computación(2)
Programación informática, programas, datos, seguridad(2)
Análisis(1)
Área de conocimiento
Aprendizaje automático(6)
Ciencias de la computación(6)
Estadísticas(2)
Optimización matemática(2)
Análisis de datos(1)
Origen
scopus(7)
Generalized 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