This paper introduces design principles for modular Bayesian fusion systems which can (i) cope with large quantities of heterogeneous information and (ii) can adapt to changing co...
Gregor Pavlin, Patrick de Oude, Marinus Maris, Jan...
An original methodology, called backward model tracing to model student performance which features a profitable integration of the bug collection and bug construction techniques i...
Abstract--Since several years, great distribution firms implement more and more complex layout and shelf allocation strategies, so as to force empirical know-how to combine with Ar...
ing from Robot Sensor Data using Hidden Markov Models Laura Firoiu, Paul Cohen Computer Science Department, LGRC University of Massachusetts at Amherst, Box 34610 Amherst, MA 01003...
The objective of this paper is to study the existing methods for unsupervised object recognition and image categorization and propose a model that can learn directly from the outp...