We boost the efficiency and robustness of distributionbased matching by random subsampling which results in the minimum number of samples required to achieve a specified probabili...
It has been demonstrated that basic aspects of human visual motion perception are qualitatively consistent with a Bayesian estimation framework, where the prior probability distri...
In the general classification context the recourse to the so-called Bayes decision rule requires to estimate the class conditional probability density functions. In this paper we p...
In this paper, we present a lower-bound estimate for dynamic time warping (DTW) on time series consisting of multi-dimensional posterior probability vectors known as posteriorgram...
We study complexity and approximation of queries in an expressive query language for probabilistic databases. The language studied supports the compositional use of confidence com...