Semi-supervised clustering uses a small amount of supervised data to aid unsupervised learning. One typical approach specifies a limited number of must-link and cannotlink constra...
This paper presents a general framework for adapting any generative (model-based) clustering algorithm to provide balanced solutions, i.e., clusters of comparable sizes. Partition...
We present an architecture of a trust framework that can be utilized to intelligently tradeoff between security and performance in a SAN file system. The primary idea is to diffe...
Aameek Singh, Sandeep Gopisetty, Linda Duyanovich,...
We extend the problem of association rule mining – a key data mining problem – to systems in which the database is partitioned among a very large number of computers that are ...
In this paper, we investigate a problem of predicting what images are likely to appear on the Web at a future time point, given a query word and a database of historical image str...