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Introduction to Semi-Supervised Learning
Semi-supervised learning is a learning paradigm concerned with the study of how computers and natural systems such as humans learn in the presence of both labeled and unlabeled data. Traditionally, learning has been studied either in the unsupervised paradigm (e.g., clustering, outlier detection) wh...
| Clasificación: | Libro Electrónico |
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| Autores principales: | , |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cham :
Springer International Publishing : Imprint: Springer,
2009.
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| Edición: | 1st ed. 2009. |
| Colección: | Synthesis Lectures on Artificial Intelligence and Machine Learning,
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| Temas: | |
| Acceso en línea: | Texto Completo |
Tabla de Contenidos:
- Introduction to Statistical Machine Learning
- Overview of Semi-Supervised Learning
- Mixture Models and EM
- Co-Training
- Graph-Based Semi-Supervised Learning
- Semi-Supervised Support Vector Machines
- Human Semi-Supervised Learning
- Theory and Outlook.