courses:xep33sml:materials:lectures [CourseWare Wiki]

Lect.	Lecturer	Topic	Additional reading
01	BF	Markov Random Fields & Gibbs Random Fields
02	BF	The most probable realisation of a GRF	[Savchynskyy19]
03	BF	Belief Networks & Stochastic Neural Networks
04	VF	Empirical Risk Minimization
05	VF	Structured Output Linear Classifier and Perceptron
06	VF	Learning max-sum classifier by Perceptron
07	VF	Structured Output Support Vector Machines
08	VF	Cutting Plane Algorithm
09	VF	Learning Max-Sum classifier by SO-SVM
10	BF	Maximum Likelihood learning for MRFs I	updated on 4.5.22
11	BF	Maximum Likelihood learning for MRFs II
12	BF	Variational Autoencoders