We propose a new matrix completion algorithm— Kernelized Probabilistic Matrix Factorization (KPMF), which effectively incorporates external side information into the matrix fac...
Large graph analysis has become increasingly important and is widely used in many applications such as web mining, social network analysis, biology, and information retrieval. The...
With very noisy data, having plentiful samples eliminates overfitting in nonlinear regression, but not in nonlinear principal component analysis (NLPCA). To overcome this problem...
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
The recent emergence of dramatically large computational power, spanning desktops with multicore processors and multiple graphics cards to supercomputers with 105 processor cores,...