We develop a probabilistic modeling framework for multiway arrays. Our framework exploits the link between graphical models and tensor factorization models and it can realize any ...
In this paper, we study probabilistic modeling of heterogeneously attributed multi-dimensional arrays. The model can manage the heterogeneity by employing an individual exponential...
Matrix factorization algorithms are frequently used in the machine learning community to find low dimensional representations of data. We introduce a novel generative Bayesian pro...
There has been an increased demand for characterizing user access patterns using web mining techniques since the informative knowledge extracted from web server log files can not ...
Energy-based learning (EBL) is a general framework to describe supervised and unsupervised training methods for probabilistic and non-probabilistic factor graphs. An energy-based ...