courses:xep33sml:materials:lectures [CourseWare Wiki]

Lect.	Lecturer	Topic
01	BF	Convex optimisation I
02	BF	Convex optimisation II
03	BF	Markov Random Fields & Gibbs Random Fields
04	BF	Estimating marginal probabilities
05	BF	Estimating marginal probabilities
06	BF	Maximum Likelihood learning for MRFs (supervised case)
07	BF	Maximum Likelihood learning for MRFs (unsupervised case)
08	VF	Discriminative structured output learning, Perceptron algorithm
09	VF	Learning max-sum classifier by Perceptron
10	VF	Structured Output Support Vector Machines
11	VF	Batch Solvers for Convex Risk Minimization
12	VF	Online Solvers for Convex Risk Minimization
13	BF	Applications: Computer Vision