Semi-supervised learning has emerged as a popular framework for improving modeling accuracy while controlling labeling cost. Based on an extension of stochastic composite likeliho...
Joshua Dillon, Krishnakumar Balasubramanian, Guy L...
We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
The problem of automatically filtering out spam e-mail using a classifier based on machine learning methods is of great recent interest. This paper gives an introduction to mach...
Bart Massey, Mick Thomure, Raya Budrevich, Scott L...
In this paper, we propose a new approach for identifying the language type of character images. We do this by classifying individual character images to determine the language bou...
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...