Background: Despite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges i...
Chris Tomlinson, Manjula Thimma, Stelios Alexandra...
The application of frequent patterns in classification appeared in sporadic studies and achieved initial success in the classification of relational data, text documents and graph...
Traditional problem determination techniques rely on static dependency models that are difficult to generate accurately in today’s large, distributed, and dynamic application e...
Mike Y. Chen, Emre Kiciman, Eugene Fratkin, Armand...
The frequent items problem is to process a stream of items and find all items occurring more than a given fraction of the time. It is one of the most heavily studied problems in d...
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. In many cases, regression algori...