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Maximum-likelihood for regression and classification: an overview

23 November 2017
San Francesco - Via della Quarquonia 1 (Classroom 2 )
The objective of this seminar is to provide an overview on commonly used maximum-likelihood algorithms, such as linear regression, logistic regression and Naive Bayes classifiers. Numerical implementation aspects will be also discussed. Finally, a novel optimization-based algorithm for training Markov jump models will be presented, empathising its maximum-likelihood interpretation.