We present a method to represent unstructured scalar fields at multiple levels of detail. Using a parallelizable classification algorithm to build a cluster hierarchy, we generate...
Document classification presents difficult challenges due to the sparsity and the high dimensionality of text data, and to the complex semantics of the natural language. The tradi...
We consider the problem of approximating a family of isocontours in a sensor field with a topologically-equivalent family of simple polygons. Our algorithm is simple and distribu...
We describe a new approach for creating concise high-level generative models from range images or other approximate representations of real objects. Using data from a variety of a...
Concise representations of frequent itemsets sacrifice readability and direct interpretability by a data analyst of the concise patterns extracted. In this paper, we introduce an...