Large sensor networks are being widely deployed for measurement, detection, and monitoring applications. Many of these applications involve database systems to store and process d...
In kernel density estimation methods, an approximation of the data probability density function is achieved by locating a kernel function at each data location. The smoothness of ...
We apply a multi-target recursive Bayes filter, the Probability Hypothesis Density (PHD) filter, to a visual tracking problem: tracking a variable number of human groups in video....
Ya-Dong Wang, Jian-Kang Wu, Ashraf A. Kassim, Weim...
Naive Bayes models have been widely used for clustering and classification. However, they are seldom used for general probabilistic learning and inference (i.e., for estimating an...
We present a framework for interfacing a PCFG parser with lexical information from an external resource following a different tagging scheme than the treebank. This is achieved by...
Yoav Goldberg, Reut Tsarfaty, Meni Adler, Michael ...