In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
Large, high dimensional data spaces, are still a challenge for current data clustering methods. Frequent Termset (FTS) clustering is a technique developed to cope with these chall...
We consider a problem known as the restricted assignment version of the max-min allocation problem with indivisible goods. There are n items of various nonnegative values and m pl...
Although techniques to automatically generate metadata have been steadily refined over the past decade, archive professionals at radio broadcasters continue to use conventional au...
Logistic models are arguably one of the most widely used data analysis techniques. In this paper, we present analyses focussing on two important aspects of logistic models—its r...