A novel center-based clustering algorithm is proposed in this paper. We first formulate clustering as an NP-hard linear integer program and we then use linear programming and the ...
In knowledge discovery applications, where new features are to be added, an acquisition policy can help select the features to be acquired based on their relevance and the cost of...
In semi-supervised clustering, domain knowledge can be converted to constraints and used to guide the clustering. In this paper we propose a feature selection algorithm for semi-s...
We introduce a new class of Reinforcement Learning algorithms designed to operate in perceptual spaces containing images. They work by classifying the percepts using a computer vi...
Abstract. In this paper, feature selection methodology from the machine learning literature is applied to the problem of shape-based classification. This methodology discards stati...
Paul A. Yushkevich, Sarang C. Joshi, Stephen M. Pi...