In this paper, a fast adaptive neural network classifier named FANNC is proposed. FANNC exploits the advantages of both adaptive resonance theory and field theory. It needs only on...
This paper presents a novel approach to representing 2-d shapes that adaptively models different portions of the shape at different resolutions, having higher resolution where it ...
Kaushik Chakrabarti, Michael Ortega-Binderberger, ...
In multiple instance learning (MIL), how the instances determine the bag-labels is an essential issue, both algorithmically and intrinsically. In this paper, we show that the mech...
— We consider nonlinear detection in rank-deficient multiple-antenna assisted beamforming systems. By exploiting the inherent symmetry of the underlying optimal Bayesian detecti...
In this paper, we present a dynamically reconfigurable cache architecture using adaptive block allocation policy analyzed by means of simulation. Our main objectives are: to propo...