Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
Given the increasing traffic on the World Wide Web (Web), it is difficult for a single popular Web server to handle the demand from its many clients. By clustering a group of Web ...
We investigate the management of flocking mobile objects using a parallel message-passing computer cluster. An octree, a data structure well-known for use in managing a 3D space, ...
Gradient Boosted Regression Trees (GBRT) are the current state-of-the-art learning paradigm for machine learned websearch ranking — a domain notorious for very large data sets. ...
Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal...
Clusters of workstations have become a cost-effective means of performing scientific computations. However, large network latencies, resource sharing, and heterogeneity found in ...