Courses:

Statistical Learning Theory and Applications >> Content Detail



Lecture Notes



Lecture Notes

This section contains documents that could not be made accessible to screen reader software. A "#" symbol is used to denote such documents.

All materials are courtesy of the person named and are used with permission.


SES #TOPICSSUMMARYSLIDES
1The Course at a Glance(PDF)(PDF - 8.10 MB)
2The Learning Problem in Perspective(PDF)(PDF)
3Reproducing Kernel Hilbert Spaces(PDF)(PDF)
4Regression and Least-Squares Classification(PDF)(PDF)
5Support Vector Machines for Classification(PDF)(PDF)
6Manifold Regularization(PDF)(PDF)
7Unsupervised Learning Techniques(PDF)(PDF)
8Multiclass(PDF)(PDF)
9Ranking(PDF)(PDF)#
10Boosting and Bagging(PDF)(PDF)
11Computer Vision

Object Detection
12Online Learning(PDF)(PDF)
13Loose Ends

Project Discussions
14Generalization Bounds

Introduction to Stability
(PDF)(PDF)
15Stability of Tikhonov Regularization(PDF)(PDF)
16Uniform Convergence Over Function Classes(PDF)(PDF)
17Uniform Convergence for Classification

VC-dimension
(PDF)(PDF)
18Neuroscience(PDF)(PDF - 2.5 MB)#
19Symmetrization

Rademacher Averages
20Fenchel Duality
21Speech / Audio
22Active Learning(PDF)
23Morphable Models for Video
24Bioinformatics
25Project Presentations
26Project Presentations (cont.)
Math Camp 1: Functional Analysis(PDF)
Math Camp 2: Probability Theory(PDF)

 








© 2009-2020 HigherEdSpace.com, All Rights Reserved.
Higher Ed Space ® is a registered trademark of AmeriCareers LLC.