Description

The goal of this course is to give an introduction to fundamental models and techniques in graduate-level modern discrete probability. Topics are taken mostly from probability on graphs: percolation, random graphs, Markov random fields, random walks on graphs, etc. No attempt is made at covering these areas in depth. Rather the emphasis is on developing and illustrating common and important techniques. Various applications, in particular in the theoretical foundations of data science and machine learning, are also discussed along the way.

General Information

Time and place
MWF 11:00 AM - 11:50 AM
B119 Van Vleck Hall
Instructor
Sebastien Roch
Use Piazza for all communications
Office hours
To be announced
Office hours will start after Sep 11

Announcements

Third homework assignment has been posted on Canvas
12/4/2023, 6:21:25 PM
In-person lecture today (Nov 22)
11/22/2023, 8:30:22 AM

There will be an in-person lecture today in 833. 

(I will be coming over from a defense on the other side of campus, so I may be a little late.)

Video lecture for Nov 20
11/20/2023, 10:45:14 AM
No in-person lecture today (Oct 20)
10/20/2023, 8:48:34 AM

There is no in-person lecture today. Instead, see @23.

Tentative Schedule
9/13/2023, 1:20:06 PM

Here is a tentative schedule. It refers to sections from the notes on the course website.

Dec 13: 4.3 continued

Dec 11: 4.3 continued

Dec 8: 4.2.4 continued, 4.3

Dec 6: 4.2.3 continued, 4.2.4

Dec 4: 4.2.2 continued, 4.2.3

Dec 1: 4.2.1 continued, 4.2.2

Nov 29: 4.2.1

Nov 27: 4.1 continued

Nov 22: 5.3.4 continued, 5.1.4

Nov 20: 4.1

Nov 17: 5.3.4

Nov 15: 5.3.1

Nov 13: 5.2.3 continued, beginning of 5.3

Nov 10: 5.2.3

Nov 8: parts of 4.1.3., 5.2.2 continued

Nov 6: 5.2.1 continued, 5.2.2

Nov 3: 5.2.1

Nov 1: parts of 3.3.3 , beginning of 5.2

Oct 30: parts of 3.3.3 

Oct 27: parts of 3.3.3

Oct 25: parts of 3.3.2

Oct 23: parts of 3.3.2

Oct 20: 5.1

Oct 18: 3.3.1

Oct 16: 3.3.1

Oct 13: 3.1.2, 3.1.3

Oct 11: 1.1.2, 3.1.1, 3.1.2

Oct 9: 3.2.4

Oct 6: 3.2.1 and 3.2.2

Oct 4: 3.2.1 and 3.2.2

Oct 2: finish 2.4.4, parts of 3.1

Sep 29: continue 2.4.4

Sep 27: parts of 2.4.5, start 2.4.4

Sep 25: finish 2.4.2

Sep 22: 2.4.2

Sep 20: 2.4.2

Sep 18: 2.4.1, 2.4.2

Sep 15: finish 2.3.2

Sep 13: 2.3.1, 2.3.2

Sep 11: 2.2.1, 2.2.2

Video links for Sep 6 and 8
8/30/2023, 11:33:00 AM

Instead of lectures on Sep 6 and 8, please watch the following 4 videos:

1) Welcome + Syllabus 

2) Overview (slides here)

3) Review of Markov Chains (slides here)

4) Review of Martingales (slides here)

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Background and review materials
8/29/2023, 11:48:29 AM

I will assume that you are generally familiar with basic stochastic processes, primarily Markov chains and martingales, and that you have been exposed to rigorous, measure-theoretic probability. E.g., the courses MATH/STAT 632 and MATH/STAT 733 or 709 will suffice. If you need a refresher, check out Chapter 1 and Appendix B in the lecture notes.

 

Lecture notes
8/29/2023, 11:29:10 AM

The notes for the course are available on the following website:

https://people.math.wisc.edu/~roch/mdp/index.html

Staff Office Hours
NameOffice Hours
Sebastien Roch
When?
Where?