Schedule for Machine Learning (308-761A)

Fall 2001

All the lecture notes will be linked to this web page, in PDF and postscript format. The reader for PDF files is available free from Adobe for UNIX, Apple Macintosh, and Windows. You can view both postscript and PDF files using ghostview. For printing convenience, a postscript format having 4 slides per page will also be included (marked PS4).

Tentative Schedule

Lec.
Date
Topic
Readings
Notes
1
Sep. 6
  Introduction  Mitchell, Chapter 1
 Slides: PS, PDF		  
2
Sep. 11
  Concept Learning and Version Spaces  Mitchell, Chapter 2
 Slides: PS, PDF		  
3
Sep. 13
  PAC learning  Mitchell, sections 7.1-7.3.
 Slides: PS, PDF
  Homework 1 Posted
PS, PDF
4
Sep. 18
  Decision Trees - Part I  Mitchell, Chapter 3
 Slides: PS, PDF 		 
5
Sep. 20
  Decision Trees - Part II  Mitchell, Chapter 3
 Slides: PS, PDF
  Homework 1 Due!
  Reading 1 Posted
6
Sep. 25
  Artificial Neural Networks - Part I  Mitchell, Chapter 4
 Slides: PS, PDF
  Reading 1 Due!
7
Sep. 27
  Artificial Neural Networks - Part II  Mitchell, Chapter 4
 Slides: PS, PDF 		 
8
Oct. 2
  VC Dimension  Mitchell, section 7.4
 
  Homework 2 Posted
PS, PDF
9
Oct. 4
  Empirical Evaluation: Experiment design, Statistical tests  Mitchell, Chapter 5
 		  
10
Oct. 9
  Empirical Evaluation: ANOVA, Non-parametric tests
 Instance-Based Learning 		 Mitchell, Chapter 8
 
 
11
Oct. 11
  Bayesian Learning  Mitchell, sections 6.1 - 6.10
 
  Homework 2 Due!
Homework 3 Posted
12
Oct. 16
  No lecture    
13
Oct. 18
  Support Vector Machines - I  
 		    
14
Oct. 23
  Support Vector Machines - II  
 
  Homework 3 Due!
  Reading 2 Posted
15
Oct. 25
  Ensemble Classifiers TBA
 Reading 2 Due!
Reading 3 posted
16
Oct. 30
  Introduction to Reinforcement Learning  Barto & Sutton, Chapters 1 and 3
 Slides: PS, PDF
Reading 3 due!
17
Nov. 1
  Markov Decision Processes  Barto & Sutton, Chapters 3, 4 and Sec.5.1-5.2
 Slides: PS, PDF		  
18
Nov. 6
  Temporal-difference learning  Barto & Sutton, Sec. 6.1-6.5
 Slides: Powerpoint
  Project proposal due! 
19
Nov. 8
  No lecture (Blanchette talk)    
20
Nov. 13
  Eligibility traces   Barto & Sutton,Chapter 7
 Slides: PS, PDF
  Homework 4 Posted
PS, PDF
21
Nov. 15
  Function approximation in reinforcement learning  Barto & Sutton,Chapter 8
 Slides: PS, PDF 		 
22
Nov. 20
  Evolutionary Learning  Mitchell, Chapter 9
 Slides: PS, PDF		  
23
Nov. 22
  Unsupervised Learning  TBA
 
Reading 4 posted
24
Nov. 27
  Unsupervised Learning - II  
 
  Reading 4 Due!
25
Nov. 29
  Machine learning: present and future
 Project presentation: Pavel
 Class evaluation forms
  Homework 4 Due!
  
26
Dec. 4
  Project presentations: Kaleigh, Ondrej, Feng, Eric, Hugo  
 
 
Extra
Dec. 6
  Project presentations: Marina, Linqiao, Vik, Ligen, Mark, Andy, Nic, Rhodes, John  
 
 
Prof. Doina PRECUP
Last modified: Thu Nov 22 17:21:06 EST 2001