Documentos de A. E. Castro-Ospina | REDI

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Filtros aplicados

Área de conocimiento: "Algoritmo"

Subtipo de publicación

Conference Object(5)

Publisher

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)(3)

Communications in Computer and Information Science(1)

Pattern Recognition Letters(1)

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS(1)

Sensors (Switzerland)(1)

Área temáticas

Ciencias de la computación(4)

Funcionamiento de bibliotecas y archivos(2)

Métodos informáticos especiales(2)

Programación informática, programas, datos, seguridad(2)

Biblioteconomía y Documentación informatica(1)

Área de conocimiento

Aprendizaje automático(5)

Ciencias de la computación(3)

Optimización matemática(1)

Año de Publicación

Origen

Palabras Claves

Multimodality(2)

Normalized cut clustering(2)

Spectral clustering(2)

multiple kernel learning(2)

Eigenvectors(1)

Automatic graph building approach for spectral clustering

Conference Object

Abstract: Spectral clustering techniques have shown their capability to identify the data relationships using

Palabras claves:

Graph analysis, kernel function, Spectral clustering

A. E. Castro-Ospina, Álvarez-Meza A.M., Castellanos-Dominguez G.

Automatic graph pruning based on kernel alignment for spectral clustering

Abstract: Detection of data structures in spectral clustering approaches becomes a difficult task when dealing

Palabras claves:

Graph pruning, Kernel alignment, Spectral clustering

A. E. Castro-Ospina, Álvarez-Meza A.M., Castellanos-Dominguez G.

A novel method for objective selection of information sources using multi-kernel SVM and local scaling

Abstract: Advancement on computer and sensing technologies has generated exponential growth in the data availa

Palabras claves:

Machine learning, Multimodality, multiple kernel learning, Source selection, SUPPORT VECTOR MACHINES

A. E. Castro-Ospina, Areiza-Laverde H.J., Díaz G.M., Hernández M.L.

Developments on solutions of the normalized-cut-clustering problem without eigenvectors

Conference Object

Abstract: Normalized-cut clustering (NCC) is a benchmark graph-based approach for unsupervised data analysis.

Palabras claves:

Eigenvectors, Graph-based clustering, Normalized cut clustering, Quadratic forms

A. E. Castro-Ospina, Diego Hernán Peluffo-Ordóñez, Israel D. Herrera-Granda, K. L. Ponce-Guevara, Leandro L. Lorente-Leyva, Miguel A. Becerra, Paul D. Rosero-Montalvo, Rodríguez-Sotelo J.L.

Feature group selection using mkl penalized with ℓ<inf>1</inf> -norm and svm as base learner

Conference Object

Abstract: Objective feature selection is an important component in the machine learning framework, which has a

Palabras claves:

feature selection, Group LASSO, Multimodality, multiple kernel learning, sparsity

A. E. Castro-Ospina, Areiza-Laverde H.J., Díaz G.M.

Efficient hyperparameter optimization in convolutional neural networks by learning curves pbkp_rediction

Conference Object

Abstract: In this work, we present an automatic framework for hyperparameter selection in Convolutional Neural

Palabras claves:

deep learning, forecasting, Hyperparameter optimization, Learning curves, Singular spectrum analysis, SVR

A. E. Castro-Ospina, Cardona-Escobar A., Giraldo-Forero A., Jaramillo-Garzon J.A.

Novel heuristic search for ventricular arrhythmia detection using normalized cut clustering

Conference Object

Abstract: Processing of the long-term ECG Holter recordings for accurate arrhythmia detection is a problem tha

Palabras claves:

cardiac arrhythmia, heuristic search, kernel density estimator, Normalized cut clustering

A. E. Castro-Ospina, Castellanos-Dominguez G., Castro-Hoyos C., Diego Hernán Peluffo-Ordóñez