Schedule
| Day | Session 1 | Session 2 | Session 3 |
|---|---|---|---|
| Monday 13 June | Introduction to Machine Learning Wray Buntine | Introduction to Graphical Models Tomi Silander | Kernel methods Chiranjib Bhattacharyya |
| Tuesday 14 June | How We Represent Text? ...From Characters to Logic Marko Grobelnik | Learning to Rank Hang Li | Multi-Source Learning; Theory and Application David Hardoon |
| Wednesday 15 June | Partially Observable Markov Decision Processes Wee Sun Lee | Feature Selection using Structural SVM and its Applications Ivor Tsang | Banquet at Guild House, NUS |
| Thursday 16 June | Probabilistic Models for Computational Linguistics Mark Johnson | Bayesian Nonparametrics Yee Whye Teh | Gaussian Processes, Graphical Model Structure Learning Zoubin Ghahramani |
| Friday 17 June | Markov Random Fields for Computer Vision Stephen Gould | Learning in Markov Random Fields Max Welling | Transfer Learning Qiang Yang and Sinno Pan |
The timing for the daily schedule is as follows (note timing difference for Wednesday):
- 9.00-10.30am: Session 1 (9.30-10.45am Wednesday)
- 10.30-10.45am: Morning tea (10.45-11am Wednesday)
- 10.45-12noon: Session 1 continued (11-12.30am Wednesday)
- 12noon-1.15pm: Lunch time (12.30-2pm Wednesday)
- 1.15-4.00pm: Session 2 (2-4.45pm Wednesday)
- 4.00-4.30pm: Afternoon tea
- 4.30-7.15pm: Session 3 (Banquet 6pm Wednesday)