This paper investigates the problem of incorporating auxiliary information (e.g. pitch) for speech recognition using dynamic Bayesian networks (DBNs). Previous works usually model...
A major difficulty in building Bayesian network models is the size of conditional probability tables, which grow exponentially in the number of parents. One way of dealing with th...
We present two Bayesian algorithms CD-B and CD-H for discovering unconfounded cause and effect relationships from observational data without assuming causal sufficiency which prec...
Subramani Mani, Constantin F. Aliferis, Alexander ...
We present two algorithms for learning large-scale gene regulatory networks from microarray data: a modified informationtheory-based Bayesian network algorithm and a modified asso...
Zan Huang, Jiexun Li, Hua Su, George S. Watts, Hsi...
Matrix factorization is a fundamental technique in machine learning that is applicable to collaborative filtering, information retrieval and many other areas. In collaborative fil...