This paper presents a system for autonomous information gathering in an information rich domain under time and monetary resource restrictions. The system gathers information using ...
Bayesian principal component analysis (BPCA), a probabilistic reformulation of PCA with Bayesian model selection, is a systematic approach to determining the number of essential p...
Abstract. Many interesting problems in computer vision can be formulated as a minimization problem for an energy functional. If this functional is given as an integral of a scalar-...
Sleep-wake protocols are critical in sensor networks to ensure long-lived operation. However, an open problem is how to develop efficient mechanisms that can be incorporated with ...
This paper proposes a novel clustering analysis algorithm based on principal component analysis (PCA) and self-organizing maps (SOMs) for clustering the gene expression patterns. T...