EECE703 Speical Topics in AI: Dimensionality Reduction, Spring 2009


  • Announcements

  • Lectures

    Dates and Titles Topics Lecture Slides Suggested Further Readings
    Lecture 0
    Welcome Introduction
    • Introduction


    Lecture 1
    Kernel PCA/ICA
    • PCA
    • Kernel PCA
    • ICA
    • CCA
    • Kernel ICA


    Lecture 2
    Multidimensional scaling
    • Metric MDS
    • Non-metric MDS
    • Landmark MDS
    • Nystrom approximation


    Lecture 3
    Manifold learning
    • Isomap
    • Locally linear embedding
    • Laplacian eigenmap
    • Locality preserving projection


    Lecture 4
    Supervised embedding
    • Marginal Fisher analysis
    • Local Fisher discriminant analysis


    Lecture 5
    Semi-supervised learning
    • Label propagation
    • Semi-supervised learning on manifolds


  • Homework Assignments