320 Pages
by
Chapman & Hall
322 Pages
by
Chapman & Hall
320 Pages
by
Chapman & Hall
Also available as eBook on:
The rapid advancement in the theoretical understanding of statistical and machine learning methods for semisupervised learning has made it difficult for nonspecialists to keep up to date in the field. Providing a broad, accessible treatment of the theory as well as linguistic applications, Semisupervised Learning for Computational Linguistics offers self-contained coverage of semisupervised... Read more
Introduction. Self-Training and Co-Training. Applications of Self-Training and Co-Training. Classification. Mathematics for Boundary-Oriented Methods. Boundary-Oriented Methods. Clustering. Generative Models. Agreement Constraints. Propagation Methods. Mathematics for Spectral Methods. Spectral Methods. Bibliography.
Index.
Index.
Biography
Abney, Steven
