# ECE 66200 Pattern Recognition and Decision Making

Course Description: ECE 66200 Pattern Recognition and Decision Making

Textbook: Introduction to Statistical Pattern Recognition, K. Fukunaga

Notes: course notes

Homeworks:

Topics:

Blogs:

- distances / metrics
- Why is Euclidean distance not a good metric in high dimensions, some explanation
- statistical distance: f-divergence and KL, reverse KL, Pearson, reverse Pearson, Jensen-Shannon divergences, Hellinger, total variation distances
- Bregman divergence, Bregman distance, paper1, paper2
- concentration inequalities: Chernoff bound, Hoeffding’s, Pinsker’s inequality, Azuma’s and McDiarmid’s inequality
- reproducing kernel Hilbert spaces and transfer learning, domain adaption
- notes of Optimal Transport, arXiv summary paper
- deep metric learning: a (long) survey, a summary

References: