30 search results - page 2 / 6 » Transfer Learning via Dimensionality Reduction |
NIPS
2008
13 years 6 months ago
2008
Recently, supervised dimensionality reduction has been gaining attention, owing to the realization that data labels are often available and indicate important underlying structure...
ECML
2005
Springer
13 years 10 months ago
2005
Springer
Abstract. In this paper, dimensionality reduction via matrix factorization with nonnegativity constraints is studied. Because of these constraints, it stands apart from other linea...
ICML
2008
IEEE
14 years 6 months ago
2008
IEEE
In this paper we introduce a novel approach to manifold alignment, based on Procrustes analysis. Our approach differs from "semisupervised alignment" in that it results ...
BMVC
2010
13 years 3 months ago
2010
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
ICML
2004
IEEE
14 years 6 months ago
2004
IEEE
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...