Instructor: Professor Padhraic Smyth
Lectures: Tuesdays and Thursdays,
Office Hours: Thursday, 4 to 5pm.
Course Code: 34520
In this course students will build on
the basic probability concepts learned
in Math 67 and learn how these ideas can be applied to a broad range of problems in modern computer science. The methods and models used will
be
mathematical in nature, but will be illustrated using real-world
applications.
Among the application areas that we will discuss are
modeling of
text and Web data, network traffic modeling, probabilistic analysis of
algorithms
and graphs, reliability modeling, simulation algorithms, data mining,
and
speech recognition. The mathematical methods that we will use to
analyze these
applications will include basic principles of probability such as Bayes
rule,
conditional probability, random variables, expectation, Markov chains,
and so
forth.
Note that Mathematics 67, Introduction to Probability and Statistics
for
Computer Scientists, is a prerequisite for this class.
There will be approximately 8 homeworks during the quarter. Each homework due by the end of class on the due date. Late homeworks will not be graded so please just hand in whatever you have completed by the end the class that it is due. The lowest homework score for each student for the quarter will not be counted. Solutions will be provided after homeworks have been graded each week.
You will be required to use MATLAB for some of your homework problems.
MATLAB is available on about 34 machines in the CS 364 lab - the
machines are in 3 rows front of the lab assistant's desk and to the
left of this desk as you face away from it. Note that Mikhail will be providing a tutorial on how to use MATLAB in the first discussion session on Friday the 12th of January.
For questions relating to homeworks and grading please email the TA Mikhail directly with your questions. If Mikhail cannot answer your question, he will pass it along to Professor Smyth. For other more general questions about the class, please email Professor Smyth directly.
In all emails about this class, please start the subject line with "[cs 177]....." so that we can easily keep track of class-related emails.
We will try to respond to emails as quickly as is practical, but there may occasionally be a delay of a day or so, especially on the weekends.
Academic honesty is taken seriously. For homework problems or programming assignments you are allowed to discuss the problems or assignments verbally with other class members, but under no circumstances can you look at or copy anyone else's written solutions or code relating to homework problems or programming assignments. All problem solutions submitted must be material you have personally written during this quarter. Failure to adhere to this policy can result in a student receiving a failing grade in the class. It is the responsibility of each student to be familiar with UCI's current academic honesty policies. Please take the time to read the current UCI Senate Academic Honesty Policies (in Spring Schedule of Classes, a few pages from the end). Also you may want to look at the ICS Department's policies on academic honesty .
You are asked to be respectful of your student colleagues and instructor in class, not being disruptive or otherwise distracting others in the classroom. This includes turning off cell-phones and not using your laptops during class.