The problem of nonlinear dimensionality reduction is considered. We focus on problems where prior information is available, namely, semi-supervised dimensionality reduction. It is...
Xin Yang, Haoying Fu, Hongyuan Zha, Jesse L. Barlo...
Recently the problem of dimensionality reduction has received a lot of interests in many fields of information processing. We consider the case where data is sampled from a low d...
Nonlinear dimensionality reduction is formulated here as the problem of trying to find a Euclidean feature-space embedding of a set of observations that preserves as closely as p...
Semi-definite Embedding (SDE) has been a recently proposed to maximize the sum of pair wise squared distances between outputs while the input data and outputs are locally isometri...
Benyu Zhang, Jun Yan, Ning Liu, QianSheng Cheng, Z...