15-359 Probability and Computing (SPRING 13), 12 Units
CLASS: Tu/Th 10:30 - 12:00 in GHC 4307
RECITATION A: F 10:30 - 11:30 in WEAN 5302
RECITATION B: F 11:30 - 12:30 in WEAN 5302
Probability theory has become indispensable in computer science. In
areas such as artificial intelligence and computer science theory,
probabilistic methods and ideas based on randomization are central.
In areas such as networks and systems, probability is
necessary to model variability in the arrival process and service
requirements of jobs, so that we can understand how delay increases with increasing load, predict necessary buffer sizes, determine the appropriate number of servers in a data center, and so on.
This course gives
an introduction to probability as it is used in computer science
theory and practice, drawing on applications and current research
developments as motivation and context. We will cover basic probability including discrete and continuous random variables, expectations, higher moments, Laplace and z-transforms, and joint distributions. We will also cover many advanced topics including combinatorial
probability and random graphs, heavy tail distributions, concentration
inequalities, randomized algorithms, sampling random variables
and computer simulation, discrete Markov chains and continuous-time Markov chains and their many
applications, elementary queueing theory and a look at its use in modeling the web, routers, data centers, networking protocols and more.
The course will assume some very elementary familiarity with 3D calculus and linear algebra.
This class assumes no prior Probability/Statistics classes, and will
satisfy the Computer Science Probability/Statistics requirement.
- Monday 2:30 p.m. - 3:30 p.m. (Terry -- Wean 8120)
- Tuesday 5:30 p.m. - 6:30 p.m. (Mor -- GHC 7207)
- Wednesday 4:00 p.m. - 5:00 p.m. (Victor -- GHC 7719)
- Wednesday 6:00 p.m. - 7:00 p.m. (Adrian -- GHC 4th floor TA room)
- Thursday 4 p.m. - 5:30 p.m. (Adrian -- GHC 4th floor TA room)
- Friday 2:30 p.m. - 3:30 p.m. (Terry -- Wean 8120)
- Weekly homework -- worth 35% combined.
- Midterm 1 -- worth 15%.
- Midterm 2 -- worth 15%.
- Random quizzes -- worth 10% combined. Lowest quiz is dropped. You will typically receive a warning about the quiz during the prior lecture.
- Final -- worth 25%.
TURNING IN HOMEWORK AND LATENESS POLICY:
Homework will be due each week on Friday prior to recitation
and will be returned, graded, within one week. All homework must be latexed and turned in online as a pdf file. If you need a figure, you can scan that in and include it within your latex file. Latex templates and information for turning in homework will be provided soon.
You are allowed a total of 5 late days. No more than 2 late days can be
used for each homework. It is your responsibility to deliver the late homework
to the TA. Once you have used up your 5 late days, you cannot receive any more late days, so please save these up for illnesses and interviews.
If you use an outside source (web site, book, etc.), please cite that source.
It is fine to discuss problems with others, but you need to write up
the actual homework alone. At the top of your homework sheet, please
list all the people with whom you discussed any problem.
Crediting help from other classmates will not take away any
credit from you, and will prevent us from assuming cheating if your
answers look similar to their answers. Note that the person providing answers is just as
guilty as the person receiving answers.
The above is the standard policy in all of academia.
NO LAPTOPS/CELL PHONES:
No cell phones in class. If you need to use a laptop, please sit in the back of the room, so that you do not disturb others in the class.
We expect you to take notes daily and read over your notes before class.
You should not need a text book if you do this.
There will eventually be a text book available covering class material, but the book is not out yet (maybe mid-February).
In the meantime, if you really want a book, a highly readable text is Introduction to Probability Models
by Dimitri P. Bertsekas and John N. Tsitsiklis, Athena Scientific, copyright 2008, 2nd edition.