—It is well known that the key of Bayesian classifier learning is to balance the two important issues, that is, the exploration of attribute dependencies in high orders for ensu...
Discrete mixed membership modeling and continuous latent factor modeling (also known as matrix factorization) are two popular, complementary approaches to dyadic data analysis. In...
This paper provides an overview of current and potential future spam filtering approaches. We examine the problems spam introduces, what spam is and how we can measure it. The pap...
We present an objective approach for evaluating probability elicitation methods in probabilistic models. Our method draws on ideas from research on learning Bayesian networks: if ...
Statistical learning and probabilistic inference techniques are used to infer the hand position of a subject from multi-electrode recordings of neural activity in motor cortex. Fi...
Yun Gao, Michael J. Black, Elie Bienenstock, Shy S...