In our previous work, we have developed sparse least squares support vector regressors (sparse LS SVRs) trained in the primal form in the reduced empirical feature space. In this p...
We propose a novel approach for categorizing text documents based on the use of a special kernel. The kernel is an inner product in the feature space generated by all subsequences...
Huma Lodhi, John Shawe-Taylor, Nello Cristianini, ...
A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...
Anatomical objects often have complex and varying image appearance at different portions of the boundary; and it is frequently a challenge even to select appropriate scales at whic...
Abstract--We propose an automatic method for measuring content-based music similarity, enhancing the current generation of music search engines and recommender systems. Many previo...