Decomposition Methods for Machine Learning with Small, Incomplete or Noisy Datasets

In many machine learning applications, measurements are sometimes incomplete or noisy resulting in missing features. In other cases, and for different reasons, the datasets are originally small, and therefore, more data samples are required to derive useful supervised or unsupervised classification...

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Detalles Bibliográficos
Autor principal: Caiafa, Cesar Federico
Formato: Articulo
Lenguaje:Inglés
Publicado: 2020
Materias:
Ingeniería Electrónica
Ciencias Informáticas
Empirical mode decomposition
Machine learning
Sparse representations
Tensor decomposition
Tensor completion
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/119641
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata

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