We consider a model in which background knowledge on a given domain of interest is available in terms of a Bayesian network, in addition to a large database. The mining problem is...
We address the problem of approximating the 2-Interval Pattern problem over its various models and restrictions. This problem, which is motivated by RNA secondary structure predict...
Maxime Crochemore, Danny Hermelin, Gad M. Landau, ...
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
Abstract— Community discovery has drawn significant research interests among researchers from many disciplines for its increasing application in multiple, disparate areas, inclu...
Haizheng Zhang, Baojun Qiu, C. Lee Giles, Henry C....
Classification algorithms typically induce population-wide models that are trained to perform well on average on expected future instances. We introduce a Bayesian framework for l...