Tentative Class Schedule

NOTE: The following class schedule and deadlines are subject to change. Please check back from time to time.

Week	Date	Topic	Lecture	Deadlines/Evaluation
1	1/16/2007	Introduction	Lec1-Into
	1/18/2007	Basics of probability and linear algebra	Lec2-Basics
2	1/23/2007	Basics of clustering	Lec3-basic-cluster
	1/25/2007	Graph based clustering	Lec4-Graph-cluster
3	1/30/2007	Linear regression, ridge regression	Lec5-regression
	2/01/2007	Gaussian Process view of regression	Lec6-GP-regression
4	2/06/2007	Classification I: NN, Naïve Bayes, LDA	Lec7-basic-class
	2/08/2007	Classification II: linear SVM	Lec8-SVM-linear	Project Proposal
5	2/13/2007	Classification III: nonlinear SVM	Lec9-SVM-nonlinear
	2/15/2007	Classification IV: Multi-class SVM	Lec10-MSVM	Homework One
6	2/20/2007	Semi-supervised clustering I	Lec11-semi-clustering-I
	2/22/2007	Semi-supervised clustering II	Lec12-semi-clustering-II
7	2/27/2007	Semi-supervised classification I	Lec13-semi-classification-I
	3/1/2007	Semi-supervised classification II	Lec14-semi-classification-II
8	3/06/2007	Dimensionality reduction I	Lec15-PCA
	3/08/2007	Dimensionality reduction II	Lec16-PCA	Homework Two
3/12—3/18 Spring Break
10	3/20/2007	Feature selection		Invited lecture by Dr. Huan Liu
	3/22/2007			Exam
11	3/27/2007	Dimensionality reduction III	Lec17-CCA
	3/29/2007	Dimensionality reduction IV	Lec18-CCA
12	4/03/2007	Manifold learning I: MDS, Isomap	Lec19-Isomap
	4/05/2007	Manifold learning II: LLE	Lec20-LLE	Intermediate Project Report
13	4/10/2007	Manifold learning III: Laplacian Eigenmaps	Lec21-LaplacianEig
	4/12/2007	Manifold learning IV: A Unified Framework	Lec22-Unified
14	4/17/2007	Kernel Learning I	Lec23-kernel-I	Homework Three
	4/19/2007	Kernel Learning II	Lec24-kernel-II
15	4/24/2007	Kernel Learning III	Lec25-kernel-III
	4/26/2007	Project Presentation	schedule	Final project report
16	5/01/2007	Project Presentation	schedule