"Semi-supervised learning"

Designing various multivariate analysis at will via generalized pairwise expression

It is well known that dimensionality reduction based on multivariate analysis methods and their kernelized extensions can be formulated as generalized eigenvalue problems of scatter matrices, Gram matrices or their augmented matrices. This paper …

SemiCCA: Efficient Semi-supervised Learning of Canonical Correlations

Canonical correlation analysis (CCA) is a powerful tool for analyzing multi-dimensional paired data. However, CCA tends to perform poorly when the number of paired samples is limited, which is often the case in practice. To cope with this problem, we …

Automatic audio tag classification via semi-supervised canonical density estimation

We propose a novel semi-supervised method for building a statistical model that represents the relationship between sounds and text labels (“tags”). The proposed method, named semi-supervised canonical density estimation, makes use of unlabeled sound …