Recently, stability-based techniques have emerged as a very promising solution to the problem of cluster validation. An inherent drawback of these approaches is the computational c...
We propose an unconventional but highly effective approach
to robust fitting of multiple structures by using statistical
learning concepts. We design a novel Mercer kernel
for t...
In recent years there has been a lot of interest in designing principled classification algorithms over multiple cues, based on the intuitive notion that using more features shou...
We present a kernel-based algorithm for hierarchical text classification where the documents are allowed to belong to more than one category at a time. The classification model is...
The quality of large-scale recommendation systems has been insufficient in terms of the accuracy of prediction. One of the major reasons is caused by the sparsity of the samples, ...