Learning application-specific distance metrics from labeled data is critical for both statistical classification and information retrieval. Most of the earlier work in this area h...
This is to present work on modifying the Aleph ILP system so that it evaluates the hypothesised clauses in parallel by distributing the data-set among the nodes of a parallel or di...
Packet Classification (PC) has been a critical data path function for many emerging networking applications. An interesting approach is the use of TCAM to achieve deterministic, hi...
This paper presents a family of techniques that we call congealing for modeling image classes from data. The idea is to start with a set of images and make them appear as similar a...
Several published reports show that instancebased learning algorithms yield high classification accuracies and have low storage requirements during supervised learning application...