Social networks such as Facebook and Twitter, websites that allow us to share and store
information every day, ongoing research in different domain fields, advances in data …

This thesis investigates the recently proposed method of'Unsupervised Kernel
Regression'(UKR). The theoretical placement of this method as a means to pursue …

En este trabajo se presentan algunos esquemas de reducción de dimensión no lineal
(RDNL) basados en aprendizaje por variedades. En este sentido, se pretende identificar …

Online learning has attracted great attention due to the increasing demand for systems that
have the ability of learning and evolving. When the data to be processed is also high …

The recent advancement in data-driven computing technologies in various disciplines has
resulted in massive dimensional data being collected from multiple information sources …

Nonlinear dimensionality reduction (NLDR) methods have become useful tools for
practitioners who are faced with the analysis of high-dimensional data. Of course, not all …

High-dimensional data is ubiquitous in scientific research and industrial production fields. It
brings a lot of information to people, at the same time, because of its sparse and …

In current world scenario, storing data, audio, image and video is big challenging task. By
reducing the dimensionality of the data from the original dimension to lower dimension leads …

Algorithms on streaming data have attracted increasing attention in the past decade. Among
them, dimensionality reduction algorithms are greatly interesting due to the desirability of …