Similarity search and data mining often rely on distance or similarity functions in order to provide meaningful results and semantically meaningful patterns. However, standard dist...
Tobias Emrich, Franz Graf, Hans-Peter Kriegel, Mat...
This paper proposes a Bayesian algorithm to estimate the parameters of a smooth transition regression model. With in this model, time series are divided into segments and a linear...
We1 present a new actor-critic learning model in which a Bayesian class of non-parametric critics, using Gaussian process temporal difference learning is used. Such critics model ...
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...
Statistical density estimation techniques are used in many computer vision applications such as object tracking, background subtraction, motion estimation and segmentation. The pa...
Bohyung Han, Dorin Comaniciu, Ying Zhu, Larry S. D...