EE 595 Independent Studies On

Statistical Learning 

Fall 2005



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  1. Basic Probability and Statistics
  2. Introduction to Graphical Models
  3. Simple Graphical Models: Linear Classification and Regression
  4. Parameter Estimation for Completely Observed Graphical Models
  5. Expectation Maximization: Parameter Estimation for Incomplete Graphical Models
  6. Exact Inference on Graphical Models
  7. Multivariate Guassians
  8. Factor Analysis
  9. Hidden Markov Model
  10. Kalman Filtering and Applications in Tracking
  11. Approximate Inference on Graphical Models
  12. Model selection and Decision Theory
  13. VC Theory
  14. Support Vector Machines


Sen-ching Samson Cheung
Last modified: Tue Aug 24 11:20:57 EDT 2004