The complexity of multimedia contents is significantly increasing in the current digital world.
This yields an exigent demand for developing highly effective retrieval systems to satisfy …

Spectral mixtures observed in hyperspectral imagery often display nonlinear mixing effects.
Since most traditional unmixing techniques are based upon the linear mixing model, they …

Real-world data typically contain a large number of features that are often heterogeneous in
nature, relevance, and also units of measure. When assessing the similarity between data …

DESIGN optimization problems involving more than 20 variables and using high-fidelity
simulation models for objective function and constraint evaluation often present a …

Abstract Stochastic Neighbor Embedding (SNE) has shown to be quite promising for data
visualization. Currently, the most popular implementation, t-SNE, is restricted to a particular …

We propose a novel framework, called Markov-Lipschitz deep learning (MLDL), to tackle
geometric deterioration caused by collapse, twisting, or crossing in vector-based neural …

In the general non-linear, non-Gaussian case, the Bayesian tracking formulas lack an
analytic expression. For this reason a number of numerical approximate solutions are …

The idea of summarizing the information contained in a large number of variables by a small
number of “factors” or “principal components” has been broadly adopted in statistics. This …

Data mining techniques are becoming indispensable as the amount and complexity of
available data is rapidly growing. Visual data mining techniques attempt to include a human …

The manifold hypothesis posits that high-dimensional data often lies on a lower-dimensional
manifold and that utilizing this manifold as the target space yields more efficient …