Algorithms for learning the conditional probabilities of Bayesian networks with hidden variables typically operate within a high-dimensional search space and yield only locally op...
Due to its static nature, the inference capability of Bayesian Networks (BNs) often deteriorates when the basis of input data varies, especially in video processing applications w...
Benny P. L. Lo, Surapa Thiemjarus, Guang-Zhong Yan...
Although a large body of work are devoted to finding communities in static social networks, only a few studies examined the dynamics of communities in evolving social networks. I...
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 ...