| Lect. | Lecturer | Topic | Pdf |
| 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 | |