DaySession 1Session 2Session 3
Monday 13 JuneIntroduction to Machine Learning
Wray Buntine
Introduction to Graphical Models
Tomi Silander
Kernel methods
Chiranjib Bhattacharyya
Tuesday 14 JuneHow We Represent Text? ...From Characters to Logic
Marko Grobelnik
Learning to Rank
Hang Li
Multi-Source Learning; Theory and Application
David Hardoon
Wednesday 15 JunePartially Observable Markov Decision Processes
Wee Sun Lee
Feature Selection using Structural SVM and its Applications
Ivor Tsang
Banquet at Guild House, NUS
Thursday 16 JuneProbabilistic Models for Computational Linguistics
Mark Johnson
Bayesian Nonparametrics
Yee Whye Teh
Gaussian Processes, Graphical Model Structure Learning
Zoubin Ghahramani
Friday 17 JuneMarkov 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)