Semi-Supervised Learning
Abstract
The distribution-independent model of (supervised) concept learning due to Valiant (1984) is extended to that of semi-supervised learning (ss-learning), in which a collection of disjoint concepts is to be simultaneously learned with only partial information concerning concept membership available to the learning algorithm. It is shown that many learnable concept classes are also ss-learnable. A new technique of learning, using an intermediate oracle , is introduced. Sufficient conditions for a collection of concept classes to be ss-learnable are given.
Cite
Text
Board and Pitt. "Semi-Supervised Learning." Machine Learning, 1989. doi:10.1007/BF00114803Markdown
[Board and Pitt. "Semi-Supervised Learning." Machine Learning, 1989.](https://mlanthology.org/mlj/1989/board1989mlj-semisupervised/) doi:10.1007/BF00114803BibTeX
@article{board1989mlj-semisupervised,
title = {{Semi-Supervised Learning}},
author = {Board, Raymond A. and Pitt, Leonard},
journal = {Machine Learning},
year = {1989},
pages = {41-65},
doi = {10.1007/BF00114803},
volume = {4},
url = {https://mlanthology.org/mlj/1989/board1989mlj-semisupervised/}
}