We describe a pattern acquisition algorithm that learns, in an unsupervised fashion, a streamlined representation of linguistic structures from a plain natural-language corpus. Th...
Zach Solan, David Horn, Eytan Ruppin, Shimon Edelm...
We present a Bayesian framework for learning higherorder transition models in video surveillance networks. Such higher-order models describe object movement between cameras in the...
Background: It is of biological interest to make genome-wide predictions of the locations of DNA melting bubbles using statistical mechanics models. Computationally, this poses th...
Background: The incorporation of statistical models that account for experimental variability provides a necessary framework for the interpretation of microarray data. A robust ex...
Kevin A. Greer, Matthew R. McReynolds, Heddwen L. ...
Mining for association rules in market basket data has proved a fruitful areaof research. Measures such as conditional probability (confidence) and correlation have been used to i...