Bayesian principal component analysis (BPCA), a probabilistic reformulation of PCA with Bayesian model selection, is a systematic approach to determining the number of essential p...
Stochastic context-free grammars (SCFGs) have long been recognized as useful for a large variety of tasks including natural language processing, morphological parsing, speech reco...
We present a tutorial survey on some recent approaches to unsupervised machine learning in the context of statistical pattern recognition. In statistical PR, there are two classica...
—Identifying unusual or unique characteristics of an observed sample in useful in forensics in general and handwriting analysis in particular. Rarity is formulated as the probabi...
We analyze visibility from static sensors in a dynamic scene with moving obstacles (people). Such analysis is considered in a probabilistic sense in the context of multiple sensors...