Indiana University Bloomington

Computer Science B659
Kernel-based Methods In Machine Learning

Contact: Predrag Radivojac
Offered: Fall, 2015
Class Time: 1pm-3:30pm
Class Days: W
Days Per Week Offered: One.
Syllabus: No Syllabus Avaliable
Description: To study the theory and practice of constructing and applying kernel-based learning algorithms. Mathematical foundations, learning methodology, linear machines, dual representations, support vector classification and regression, kernel density estimation, kernel PCA, structured-output learning, applications in text mining, bioinformatics and computational social sciences.
Books: An introduction to support vector machines and other kernel-based learning methods - by N. Cristianini and J. Shawe-Taylor, Cambridge University Press 2000.
Applied/Theoretical: Balanced.
Comments: Supplementary material will be provided for several topics.