Most existing approaches for learning action models work by extracting suitable low-level features and then training appropriate classifiers. Such approaches require large amount...
This paper presents a nonparametric approach to labeling
of local image regions that is inspired by recent developments
in information-theoretic denoising. The chief novelty
of ...
We study hierarchical classification in the general case when an instance could belong to more than one class node in the underlying taxonomy. Experiments done in previous work sh...
Collaborative recommender systems are highly vulnerable to attack. Attackers can use automated means to inject a large number of biased profiles into such a system, resulting in r...
Robin D. Burke, Bamshad Mobasher, Chad Williams, R...
This paper presents an online feature selection and classification algorithm. The algorithm is implemented for impact acoustics signals to sort hazelnut kernels. The classifier, w...