act Weighting Framework for Clustering Algorithms Richard Nock Frank Nielsen Recent works in unsupervised learning have emphasized the need to understand a new trend in algorithmi...
It has long been known that Dynamic Time Warping (DTW) is superior to Euclidean distance for classification and clustering of time series. However, until lately, most research has...
In many real-world tasks of image classification, limited amounts of labeled data are available to train automatic classifiers. Consequently, extensive human expert involvement is...
Previous study has shown that mining frequent patterns with length-decreasing support constraint is very helpful in removing some uninteresting patterns based on the observation t...
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Microarray experiments have been extensively used for simultaneously measuring DNA expression levels of thousands of genes in genome research. A key step in the analysis of gene e...
Hyuk Cho, Inderjit S. Dhillon, Yuqiang Guan, Suvri...
There has been a renewed interest in understanding the structure of high dimensional data set based on manifold learning. Examples include ISOMAP [25], LLE [20] and Laplacian Eige...
Graph-based modeling has emerged as a powerful abstraction capable of capturing in a single and unified framework many of the relational, spatial, topological, and other characteri...
Several application domains such as molecular biology and geography produce a tremendous amount of data which can no longer be managed without the help of efficient and effective ...