ECE 595ML: Machine Learning I
Category
Published on
Abstract
Spring 2020 - This course is in production
Course Website: https://engineering.purdue.edu/ChanGroup/ECE595/index.html
Course Outline:
- Part 1: Mathematical Background
- Linear Regression and Optimization
- Part 2: Classification
- Methods to train linear classifiers
- Feature analysis, Geometry, Bayesian decision rule, logistic regression, perceptron algorithm, support vector machine
- Part 3: Handling Uncertainty
- Imperfect data: noisy label, unbalanced data, missing data, knowledge transfer
- Robustness study: adversarial attack and defense
- Part 4: Learning Theory
- Evaluation of a classifier.
- Feasibility of learning, VC dimension, bias-variance, validation
Bio
Stanley H. Chan is currently an assistant professor in the School of Electrical and Computer Engineering and the Department of Statistics at Purdue University.
Dr. Chan received the Ph.D. degree in Electrical Engineering and the M.A. degree in Mathematics from the University of California at San Diego, in 2011 and 2009, respectively, and the B.Eng. degree (with first class honor) in Electrical Engineering from the University of Hong Kong in 2007. Prior to joining Purdue, he was a postdoctoral research fellow at Harvard John A. Paulson School of Engineering and Applied Sciences from 2012 to 2014. His research interests include signal and image processing, applied statistics, and large-scale numerical optimization.
References
Textbook and References
- Duda, Hart and Stork, Pattern Classification, Wiley-Interscience; 2nd edition, 2000.
- Bishop, Pattern Recognition and Machine Learning, Springer, 2006.
- Abu-Mostafa, Magdon-Ismail and Lin, Learning from Data, AMLBook, 2012.
- Hastie, Tibshirani and Friedman, Elements of Statistical Learning, Springer, 2nd edition, 2009.
Pre-requesite Background References
- Linear Algebra: Gilbert Strang, Linear Algebra and Its Applications, 5th Edition
- Optimization: Stephen Boyd and Lieven Vandenberghe, Convex Optimization, Cambridge 2004.
- Probability: Dimitri Bertsekas, Introduction to Probability, Athena Scientific, 2008, 2nd Edition.
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Location
WTHR 200, Purdue University, West Lafayette, IN