Background: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors f...
Bo Chen, Minhua Chen, John William Paisley, Aimee ...
The problem of inferring haplotypes from genotypes of single nucleotide polymorphisms (SNPs) is essential for the understanding of genetic variation within and among populations, ...
Matrix factorization is a fundamental technique in machine learning that is applicable to collaborative filtering, information retrieval and many other areas. In collaborative fil...
Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7]....
Complex networks exist in a wide array of diverse domains, ranging from biology, sociology, and computer science. These real-world networks, while disparate in nature, often compr...
Haizheng Zhang, C. Lee Giles, Henry C. Foley, John...