Abstract. Recently, the variational Bayesian approximation was applied to probabilistic matrix factorization and shown to perform very well in experiments. However, its good perfor...
This paper addresses the problem of transductive learning of the kernel matrix from a probabilistic perspective. We define the kernel matrix as a Wishart process prior and construc...
A probabilistic algorithm is presented to find the determinant of a nonsingular, integer matrix. For a matrix A ¡£¢ n¤ n the algorithm requires O¥ n3¦5 ¥ logn§ 4¦5§ bit...
This paper presents a probabilistic framework for computing correspondences and fundamental matrix in the structure from motion problem. Inspired by Moisan and Stival [1], we sugg...
: Probabilistic Boolean Network (PBN) is widely used to model genetic regulatory networks. Evolution of the PBN is according to the transition probability matrix. Steady-state (lon...
Shuqin Zhang, Wai-Ki Ching, Michael K. Ng, Tatsuya...