In this paper we introduce a novel image descriptor enabling accurate object categorization even with linear models. Akin to the popular attribute descriptors, our feature vector ...
A major obstacle that decreases the performance of text classifiers is the extremely high dimensionality of text data. To reduce the dimension, a number of approaches based on rou...
The problem of ranking, in which the goal is to learn a real-valued ranking function that induces a ranking or ordering over an instance space, has recently gained attention in mac...
We present an approach for visual discrimination of children from adults in video using characteristic regularities present in their locomotion patterns. The framework employs comp...
Supervised text categorization is a machine learning task where a predefined category label is automatically assigned to a previously unlabelled document based upon characteristic...