—Restoring data operations after a disaster is a daunting task: how should recovery be performed to minimize data loss and application downtime? Administrators are under consider...
Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
Prateek Jain, Brian Kulis, Jason V. Davis, Inderji...
We address the issue of using heterogeneous treebanks for parsing by breaking it down into two sub-problems, converting grammar formalisms of the treebanks to the same one, and pa...
Clustering, in data mining, is useful to discover distribution patterns in the underlying data. Clustering algorithms usually employ a distance metric based (e.g., euclidean) simi...
In this paper we process and analyze web search engine query and click data from the perspective of the documents (URL’s) selected. We initially define possible document categor...