Statistical Pattern Recognition (Competence)

'The main objectives of this graduate course are to equipstudents with the fundamentals of statistical patternrecognition (SPR) algorithms and techniques. PR dealswith automated classification, identification, and/orcharacterisations of signals/data from various sources.Because real world data is noisy and uncertain, we willfocus on SPR techniques, with particular emphasis on thetheoretical foundations of various techniques. Topicscovered include: fundamentals of parameter estimation(maximum likelihood, maximum-a-posteriori, posteriorpredictive), supervised learning, generative models, naiveBayes, discriminative models, logistic regression, nonparametrictechniques, Bayesian decision theory.'