Stat
161/261
Introduction to Machine Learning:
Mon/Wed/Fri: 3:00-3:50am Spring 2010, Math/Sciences 5203.
www.stat.ucla.edu/~yuille/Courses/
Course
Description
This
course gives an accessible introduction to pattern analysis and machine
intelligence aimed at advanced undergraduates and graduate students.
(It is
simpler than the more advanced class Stat 231/CS 276 -- you cannot take
both courses for graduate credit).
Reading
Material
- Ethem Alpaydin: Introduction to
Machine Learning. MIT Press. 2004.
- Course notes (available on line)
- Instructor: Prof. Alan Yuille,
yuille@stat.ucla.edu, 310-267-5383, office Math Sciences 8967.
- Office Hours: Wednesday 4.00-5.00 pm
(8967 Math Sciences), or by appointment (email).
Grading
Plan: homework assignments (60% ), computer assignments (40%).
Homework 1: homework1
Homework 2: homework 2
Homework 3: homework 3
Tentative Schedule.
|
Lecture
|
Date
|
Topics
|
Reading
Materials
|
Handouts
|
|
1
|
March-29
|
Introduction to the Machine Learning:
|
Alpaydin:
Chp 1.
|
2010lecture1.pdf
|
|
2
|
March-31
|
Supervised Learning:
|
Alpaydin:
Chp 2.
2.1
|
2010lecture2.pdf
|
|
3
|
April-2
|
VC -- Dimension
|
Alpaydin:
Chp 2.
2.2-2.3
|
2010lecture3.pdf
|
|
4
|
April-5
|
Supervised Learning: (cont)
|
Alpaydin: Chp 2
2.4-2.8
|
2010lecture4.pdf
|
|
5
|
April-7
|
Bayesian Decision Theory
|
Alpaydin:
Chp 3.
|
2010lecture5.pdf
|
6
|
April-9
|
Parametric Methods
|
Alpaydin:
Chp 4 |
2010lecture6.pdf
|
|
|
7
|
April-12
|
More Parametric Methods
|
Alpaydin:
Chp 4
|
2010lecture7.pdf
|
|
8
|
April-14
|
Parametric Methods (cont)
|
Alpaydin; Chp 4
|
2010lecture8.pdf
|
9
|
April-16
|
Multivariate Methods
|
Alpaydin Chp 5.
|
2010lecture9.pdf
|
|
10
|
April-19
|
Dimension Reduction:
Principle Component Analysis
|
Alpaydin Chp 6. |
2010lecture10.pdf
|
|
11
|
April-21
|
Dimension Reduction:
Singular Value Decomposition
|
|
Same as previous lecture
|
12
|
April-23
|
Dimension Reduction:
Fisher's LDA
|
Alpaydin Chp 6
|
2010lecture11.pdf
|
|
|
13
|
April-26
|
Clustering
|
Alpaydin:
Chp 7 |
2010lecture12.pdf
|
14
|
April-28
|
Clustering
|
Alpaydin:
Chp 7
|
Same as previous lecture |
15
|
April-30
|
Non-Parameteric Methods
|
Alpaydin:
Chp 8 |
2010lecture13.pdf
|
|
|
16
|
May-3
|
Decision Trees
|
Alpaydin:
Chp 9
|
2010lecture14.pdf
|
|
17
|
May-5
|
Linear Discrimination
|
Alpaydin:
Chp 10
|
2010lecture15.pdf
|
18
|
May-7
|
Linear Discrimination, Support Vectors
and the Kernel Trick
|
Alpaydin:
Chp 10 |
Same as previous lecture
|
|
|
19
|
May-10
|
Support Vectors in Primal Space
|
Guest
Lecture: Prof. Y-N Wu.
|
|
20
|
May-12
|
Multi-Layer Perceptrons
|
Alpaydin:
Chp 11
|
2010lecture16.pdf
|
21
|
May-14
|
AdaBoost
|
Alpaydin:
Ch 15.5
|
2010lecture17.pdf
|
22
|
May-17
|
AdaBoost (cont)
|
|
2010lecture18.pdf
|
|
23
|
May-19
|
MultiClass SVM
|
|
2010lecture19.pdf
|
|
24
|
May-21
|
Hidden Markov Models
|
Alpaydin:
Ch 13 |
2010lecture20.pdf
|
|
25
|
May-24
|
Hidden Markov Models (cont)
|
Alpaydin:
Ch 13
|
Lecture 20
notes
|
26
|
May-26
|
Hidden Markov Models (cont)
|
Alpaydin:
Ch 13 |
Lecture
20 notes
|
|
27
|
May-28
|
Latent SVM
|
|
2010lecture21.pdf
|
|
|
May-31
|
Memorial Day
|
|
|
|
28
|
June-2
|
Reinforcement Learning
|
Alpaydin Ch 15
|
2010lecture22.pdf
|
|
29
|
June-4
|
Review
|
|
|
|
|
|
|
|
|
|
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