We consider the problem of dimensionality reduction, where given high-dimensional data we want to estimate two mappings: from high to low dimension (dimensionality reduction) and f...
It is well-known that for high dimensional data clustering, standard algorithms such as EM and the K-means are often trapped in local minimum. Many initialization methods were pro...
Chris H. Q. Ding, Xiaofeng He, Hongyuan Zha, Horst...
In this paper, a new kernel-based method for data visualization and dimensionality reduction is proposed. A reference point is considered corresponding to additional constraints ta...
DimStiller is a system for dimensionality reduction and analysis. It frames the task of understanding and transforming input dimensions as a series of analysis steps where users t...
Stephen Ingram, Tamara Munzner, Veronika Irvine, M...
: Probability distribution mapping function, which maps multivariate data distribution to the function of one variable, is introduced. Distributionmapping exponent (DME) is somethi...