CSE 591: Machine Learning and Applications

Lecture Hours (Spring 2007): T, TH 4:40 pm – 5:55 pm (BYAC 270)

Instructor:	Dr. Jieping Ye
Email:	Jieping.Ye@asu.edu
Office hours:	T, TH 10:00 am – 11:45 am
Telephone:	480-727-7451
TA:	Jianhui Chen
Email:	Jianhui.chen@asu.edu
Office hours:	TH 12:00 pm – 1:00 pm (BY561CA)

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Overview

Machine Learning is the study of computer systems that automatically improve their performance through experience. This is an advanced course that will focus on the recent literature on the application of machine learning to problems from a range of different areas, including bioinformatics, computer vision, and informational retrieval. After introductory lectures, subsequent classes will focus on research papers, usually one to two papers per class. Main topics include:        

• Clustering
• Regression
• Classification
• Semi-supervised learning
• Feature reduction
• Manifold learning
• Ranking
• Kernel learning

This course should leave you with a good knowledge of state-of-the-art machine learning techniques, and an understanding of which tools are appropriate for which tasks in real-world applications.

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Course Materials:

• Lecture Notes
• Homework
• Reference
• Course Syllabus

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Useful Links:

· Kernel Machines: A central source of information on kernel based methods

· Conferences: NIPS, ICML, AISTATS

· Journals: Machine Learning, Journal of Machine Learning Research, IEEE TPAMI