Machine Learning
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1 Introduction
2 Basic Statistics
3 Instance based methods
4 Perceptron
5 Support Vectors
6 Kernels
7 Kernels
8 Stochastic Convergence
9 Tail Bounds
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18 Latent Variables II
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1 Statistics
2 Linear Algebra
3 Optimization
4 Model Selection
5 Convergence Bounds
6 Kernels
7 Risk. Gaussian Processes
8 Exponential Families
9 Information Theory
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Alex Smola
Barnabas Poczos
Ina Fiterau
Junier Oliva
Leila Wehbe
Mu Li
Xuezhi Wang
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CMU

Kernels (Recitation)

Introduction to Machine Learning - 10-701/15-781

Content

  • SVM Formulation

  • The Kernel Trick

  • Reproducing Property

Supplementary material

PDF slides for Kernels.

If you want to extract the equations from the slides you can do so by using LaTeXit, simply by dragging the equation images into it.

Videos

Unedited video straight from a GF2.