Lectures
The slides and resources for each lecture will be updated after the class. The schedule below is tentative and both the order and the content will almost definitely change as the semester goes along.
| Date | Lecture |
| 19-Jan | Introduction |
| 21-Jan | Review: Supervised Learning |
| 26-Jan | Multiclass Classification: Local models |
| 28-Jan | Multiclass Classification: Global models |
| 2-Feb | First Look at Structures |
| 4-Feb | Sequence Models: HMM |
| 9-Feb | Sequence Models: Local models |
| 11-Feb | Sequence Models: CRFs |
| 16-Feb | Sequence Models: Structured Perceptron |
| 18-Feb | General Formulations: Graphical Models |
| 23-Feb | General Formulations: Markov Logic Networks |
| 25-Feb | General Formulations: Constrained Conditioned Models |
| 2-Mar | Buffer lecture |
| 4-Mar | Project planning |
| 9-Mar | Project planning |
| 11-Mar | Training strategies: Structural SVM |
| 16-Mar | Training strategies: Structural SVM, SGD |
| 18-Mar | Inference: Graph algorithms |
| 23-Mar | Inference: ILP Inference |
| 25-Mar | Inference: Approximate Inference |
| 30-Mar | Inference: Learning to Search |
| 1-Apr | Deep learning: Neural network review |
| 6-Apr | Deep learning: Recurrent Networks, LSTM |
| 13-Apr | Deep learning and structures |
| 15-Apr | Learning latent variables |
| 20-Apr | Learning with constraints |
| 22-Apr | Buffer lecture |
| 27-Apr | Practical concerns |
| Looking back | |
| 5-May | Project presentations during final exam (8:00 AM - 10:00 AM) |
Important dates
| Date | Deadline |
| 4-Feb | Project team information due |
| 18-Feb | Review 1 due |
| 25-Feb | Project proposals due |
| 16-Mar | Assignment due |
| 30-Mar | Project intermediate status report due |
| 1-Apr | Review 2 due |
| 15-Apr | Review 3 due |
| 5-May | Project presentations in class |
| 5-May | Project final report due |