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Statistical Learning Theory and Applications >> Content Detail



Calendar / Schedule



Calendar

TP = Prof. Tomaso Poggio
AR = Sasha Rakhlin
AC = Andrew Caponnetto
RR = Dr. Ryan Rifkin


SES #TOPICSLECTURERS
1The Course at a GlanceTP
2The Learning Problem in PerspectiveTP
3Reproducing Kernel Hilbert SpacesAC
4Regression and Least-Squares ClassificationRR
5Support Vector Machines for ClassificationRR
6Manifold RegularizationAC
7Unsupervised Learning TechniquesAC
8MulticlassRR
9RankingGuest Lecturer: Giorgos Zacharia
10Boosting and BaggingAR
11Computer Vision

Object Detection
Guest Lecturer: Stan Bileschi
12Online LearningGuest Lecturer: Sanmay Das and AC
13Loose Ends

Project Discussions
14Generalization Bounds

Introduction to Stability
AR
15Stability of Tikhonov RegularizationAR
16Uniform Convergence Over Function ClassesAR
17Uniform Convergence for Classification

VC-dimension
AR
18NeuroscienceGuest Lecturer: Thomas Serre
19Symmetrization

Rademacher Averages
AR
20Fenchel DualityGuest Lecturer: Ross Lippert and RR
21Speech / AudioGuest Lecturer: Jake Bouvrie
22Active LearningGuest Lecturer: Claire Monteleoni
23Morphable Models for VideoGuest Lecturer: Tony Ezzat
24BioinformaticsGuest Lecturer: Sayan Mukherjee
25Project Presentations
26Project Presentations (cont.)
Math Camp 1: Functional AnalysisAC
Math Camp 2: Probability TheoryAR

 








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