Seminar on Jan 22^th

Session 1 (13:00~15:00)

1.     Semi-Supervised Learning on Riemannian Manifolds(�ؿ�)

2.     A statistical framework for genomic data fusion(����)

3.     Forecasting Stock Prices Using a Hierarchical Bayesian Approach(����)

Session 2 (15:30~ 18:00)

1.     Choosing Multiple Parameters cont��d. (����)

2.     Independent Component Analysis (ICA) (text book review) (����)

3.     Kernel Principal Component Analysis(�׼�)

The reading materials would be distributed offline. Get ready for that!