Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. Learning ML...
Markov logic networks (MLNs) are a statistical relational model that consists of weighted firstorder clauses and generalizes first-order logic and Markov networks. The current sta...
We introduce a new model for extracting classified structural segments, such as intro, verse, chorus, break and so forth, from recorded music. Our approach is to classify signal ...
Samer A. Abdallah, Katy Noland, Mark B. Sandler, M...
With the phenomenal success of networking sites (e.g., Facebook, Twitter and LinkedIn), social networks have drawn substantial attention. On online social networking sites, link r...
Zhijun Yin, Manish Gupta, Tim Weninger, Jiawei Han
The use of several types of structural restrictions within algorithms for learning Bayesian networks is considered. These restrictions may codify expert knowledge in a given domai...