Given any collection of data cells in a data space X, consider the problem of finding the optimal partition of the data cells into blocks which are unions of cells. The algorithms...
Bradley W. Jackson, Jeffrey D. Scargle, Chris Cusa...
Dimensionality reduction plays an important role in many machine learning and pattern recognition tasks. In this paper, we present a novel dimensionality reduction algorithm calle...
Deep-layer machine learning architectures continue to emerge as a promising biologically-inspired framework for achieving scalable perception in artificial agents. State inference ...
The diameter k-clustering problem is the problem of partitioning a finite subset of Rd into k subsets called clusters such that the maximum diameter of the clusters is minimized. ...
—Discriminant feature extraction plays a central role in pattern recognition and classification. Linear Discriminant Analysis (LDA) is a traditional algorithm for supervised feat...