Statistical Learning Theory and Applications
9.520 · Brain and Cognitive Sciences · Graduate · Spring 2006
Prof. Tomaso Poggio
This course is for upper-level graduate students who are planning careers in computational neuroscience. This course focuses on the problem of supervised learning from the perspective of modern statistical learning theory starting with the theory of multivariate function approximation from sparse data. It develops basic tools such as Regularization including Support Vector Machines for regression and classification. It derives generalization bounds using both stability and VC theory. It also di…
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Prof. Tomaso Poggio. 9.520 Statistical Learning Theory and Applications. Spring 2006. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: CC BY-NC-SA 4.0.
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