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ENEE 633 / CMSC 828C: Statistical and Neural Pattern Recognition (Fall 2007)

Instructor
: Dr. Rama Chellappa
Lecture hours : 9.30 to 10.45 am (Mon, Wed)
Class room : EGR 0135
Text Book : Christopher M. Bishop, "Pattern Recognition and Machine Learning", Springer, 2006

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Class date Topic
08/29/2007 (Monday) Overview : Pattern Recognition as a decision theoretic problem, Bayes Decision theory
09/05/2007 (Wednesday)

Minimax and Neymann Pearson Criterion

09/10/2007 (Monday) Probability Distributions
09/12/2007 (Wednesday) Maximum Likelihood and Bayes Estimation
09/17/2007 (Monday) Gaussian case, Sufficient statistics, Conjugate priors
09/19/2007 (Wednesday) Error probabilities and bounds
09/24/2007 (Monday) Linear models for regression
09/26/2007 (Wednesday) Linear models for classification
10/01/2007 (Monday) Linear models for classification
10/03/2007 (Wednesday) Linear models for classification
10/08/2007 (Monday) Non-parametric techniques : Parzen estimate, Nearest neighbor estimate, Nearest neighbor (NN) rule, Convergence and error bounds of NN rule, k-NN rule
10/10/2007 (Wednesday) Kernel methods
10/15/2007 (Monday) Kernel methods
10/17/2007 (Wednesday) Midterm exam (Topics covered until 10/08/2007 will be included)
10/22/2007 (Monday)

Support Vector Machines

10/24/2007 (Wednesday) Support Vector Machines
10/29/2007 (Monday) Graphical Models
10/31/2007 (Wednesday) Graphical Models
11/05/2007 (Monday) Mixture models and Expectation Maximization (EM) Algorithm
11/07/2007 (Wednesday) Mixture models and Expectation Maximization (EM) Algorithm
11/12/2007 (Monday) Sampling methods
11/14/2007 (Wednesday) Sampling methods
11/19/2007 (Monday) Pricipal Component Analysis (PCA), Probabilistic PCA, Kernel PCA and Independent Component Analysis (ICA)
11/21/2007 (Wednesday) Wald's sequential probability ratio test
11/26/2007 (Monday) Hidden Markov Models
11/28/2007 (Wednesday) Hidden Markov Models
12/03/2007 (Monday) Clustering techniques
12/05/2007 (Wednesday) Combining Models
12/10/2007 (Monday) Review