A good distance metric is crucial for unsupervised learning from high-dimensional data. To learn a metric without any constraint or class label information, most unsupervised metr...
We develop data structures for dynamic closest pair problems with arbitrary (not necessarily geometric) distance functions, based on a technique previously used by the author for ...
A unified variational methodology is developed for classification and clustering problems, and tested in the classification of tumors from gene expression data. It is based on flu...
J. P. Agnelli, M. Cadeiras, E. G. Tabak, C. V. Tur...
A number of real-world domains such as social networks and e-commerce involve heterogeneous data that describes relations between multiple classes of entities. Understanding the n...
Taxonomies for a set of features occur in many real-world domains. An example is provided by paleontology, where the task is to determine the age of a fossil site on the basis of t...