Loading…
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...
| Call Number: | Libro Electrónico |
|---|---|
| Main Authors: | , |
| Corporate Author: | |
| Format: | Electronic eBook |
| Language: | Inglés |
| Published: |
Cham :
Springer International Publishing : Imprint: Springer,
2009.
|
| Edition: | 1st ed. 2009. |
| Series: | Synthesis Lectures on Artificial Intelligence and Machine Learning,
|
| Subjects: | |
| Online Access: | Texto Completo |
Table of Contents:
- 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.