TENTATIVE EEL 6825 COURSE OUTLINE
AUG 24 L01 Introduction
AUG 26 L02 Bayes Decision Rule, 1D example, two-class, multi-class
AUG 28 L03 Univariate Normal, multivariate, covariance matrix,
linear transforms, eigenvectors/values, plotting
AUG 31 L04 Mahalanobis distance, linear transform of,
what do discrim surfaces look like? sigma_i same
SEP 02 L05 General quadratic decision boundaries
SEP 04 L06 How to compute and estimate error
SEP 07 NO CLASS
SEP 09 L07 Maximum Liklihood estimates of mean and variance
bias, consistency
how to create arbitrary Gaussian distribs
SEP 11 L08 HW #1 Due, review linear transforms, distance is preserved
whitening, distance is not preserved
simultaneous diagonalization
SEP 14 L09 Bhat bound
Parametric classifiers, linear classifiers
linear classifier design
Fisher criterion
SEP 16 L10 linear classifiers/more interpretation
linear separable
MSE, iterative schemes
SEP 18 L11 MSE scheme
resubstitution/holdout method
test vs. training set
SEP 21 L12 Introductions to Linear Classifiers
nonlinear features
quadratic classifier
SEP 23 L13 generalization of linear bayes to multiclass,
curse of dim
bad use of test and training
SEP 25 L14 Optimal Linear Classifiers/ Fisher criterion
How much data do you need?
how much data for classifier, for estimating error?
HW #2 Due
compute Bayes error for multivariate (in general hard)
how does error change with dimension?
normals are not the only distrib (exponential example)
SEP 28 L15 Review for Exam
SEP 30 No class (Yom Kippur)
OCT 02 Exam I
OCT 05 L16 Go over Exam.
OCT 07 L17 Parzen Windows
OCT 09 L18 introduce 1-NN, k-NN
OCT 12 L19 error for 1-NN, k-NN
OCT 14 L20 resubstitution, hold-out, leave-one-out
OCT 16 L21 k-NN
OCT 19 L22 Neural Networks
OCT 21 L23 Neural Networks HW#3 due
OCT 23 L24 Neural Networks
OCT 26 L25 Neural Networks
OCT 28 L26 Neural Networks
OCT 30 L27 Neural Networks
NOV 02 L28 Neural Networks
NOV 04 L29 Neural Networks HW #4 DUE
NOV 06 L30 Review for Exam
NOV 09 EXAM II
NOV 11 NO CLASS Veteran's Day
NOV 13 NO CLASS Homecoming
NOV 16 L32 Go over exam
NOV 18 L33 Trace optimization
NOV 20 L34 Trace optimization
NOV 23 L32 Image Processing, speech processing, HW #5 DUE
NOV 25 NO CLASS THANKSGIVING
NOV 27 NO CLASS THANKSGIVING
NOV 30 AWAY
DEC 02 AWAY
DEC 04 AWAY
DEC 07 L33 FINAL PROJECTS
DEC 09 L34 FINAL PROJECTS DUE