An efficient adaptive document classification and categorization approach is proposed for personal file creation corresponding to user's specific needs and profile. This kind ...
Categorizing web-based videos is an important yet challenging task. The difficulties arise from large data diversity within a category, lack of labeled data, and degradation of vi...
This paper introduces a strategy for training ensemble classifiers by analysing boosting within margin theory. We present a bound on the generalisation error of ensembled classifi...
Huma Lodhi, Grigoris J. Karakoulas, John Shawe-Tay...
Background: Document classification is a wide-spread problem with many applications, from organizing search engine snippets to spam filtering. We previously described Textpresso, ...
Techniques for learning from data typically require data to be in standard form. Measurements must be encoded in a numerical format such as binary true-or-false features, numerica...
V. Seshadri, Raguram Sasisekharan, Sholom M. Weiss