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Organization:
   00: Syllabus

Lectures:

  1999:
    01: Maximum Entropy
    02: LDA, PCA, and ICA
    03: Linear Prediction
    04: Dynamic Programming
    05: Factor Analysis
    06: Mutual Information
    07: Bayesian Networks
    08: Iterative Algorithms
    09: Linear Regression
    10: Speaker Adaptation
    11: Discriminative Training
    12: Finite State Machines
    13: Rational Belief Networks
    14: Markov Random Fields