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 consider the problem of distributed task allocation across swarm units comprising a swarm-based system. We model task allocation as a dynamic pricing problem within a market se...
This paper studies the greedy ensemble selection family of algorithms for ensembles of regression models. These algorithms search for the globally best subset of regresmaking loca...
Ioannis Partalas, Grigorios Tsoumakas, Evaggelos V...
We consider selective classification, a term we adopt here to refer to `classification with a reject option.' The essence in selective classification is to trade-off classifi...
It has been shown that features can be selected adaptively for object tracking in changing environments [1]. We propose to use the variance of Mutual Information [2] for online fea...