Mathematical Techniques for Computer Science Applications
Warren Weaver Hall room 201.
Professor Ernest Davis
Office hours: Tue 10:00-12:00, Wed 3:00-4:00
- phone: (212) 998-3123
- office: 329 Warren Weaver Hall
The optional recitation meets Fridays 5:00-6:00, WWH 517.
Linear Algebra and Probability for Computer Science Applications ,
CRC Press, 2012.
MATLAB: An Introduction with Applications, Wiley.
Any edition is OK. Inexpensive used copies are available online.
Course code library
Online documentation for MATLAB:
Getting Started with MATLAB
Matlab freeware clones:
Students have occasionally reported incompatibilities with Octave. I have not
received any complaints about Scilab.
Class email list
You should be automatically subscribed to the
class email list
If not, go to this link, and subscribe manually.
The grader for the course will be Vishal Shah.
All programming assignments and all exercises submitted electronically
should be emailed to him at firstname.lastname@example.org.
This course gives an introduction to theory, computational techniques, and
applications of linear algebra, probability and statistics. These three
areas of continuous mathematics are critical in many parts of computer
science, including machine learning, scientific computing, computer vision,
computational biology, computational finance,
natural language processing, and computer graphics.
The course will teach a specialized language for mathematical computation,
such as MATLAB, and will discuss how the language can be used for
computation and for graphical output. No prior knowledge of linear algebra,
probability, or statistics is assumed.
Programming assignments (40% of the grade).
Biweekly exercises (10% of the grade).
Final exam. (50% of the grade).
Exercises 1 Not to hand in.
Programming Assignment 1 Due Sept. 19.
Problem Set 2 Due Oct. 3
Programming Assignment 2 Due Oct. 3
Problem Set 3 Due Oct. 17
Programming Assignment 3 Due Oct. 17
Sample Output for Programming Assignment 3
Problem Set 4 Due Oct. 31
Programming Assignment 4 Due Oct. 31
Problem Set 5 Due Nov. 14
Programming Assignment 5 Due Nov. 14
Programming Assignment 6 Due Dec. 5
The final exam will be held Thursday Dec. 19 during the regular class hour.
It will be closed book and closed notes.
Here is a list of topics . A sample exam is on
the course Blackboard site.
Part I. Introduction:
Week 1.A Introduction to MATLAB. Basic programming language features.
Davis, Chap. 1.
Part II. Linear Algebra:
Week 1.B. Vectors. Basic operations. Dot product. Vectors in MATLAB. Plotting
Davis, Chap. 2
Week 2. Matrices. Definition, fundamental properties, basic
operations. Linear transformations.
Davis, Chap. 3
Week 3. Abstract linear algebra: Linear independence, basis,
subspaces, null space.
Davis, Section 4.1.
Week 4. Solving linear equations using Gaussian elimination.
Davis, Chap 5.
Week 5+6. Geometric applications.
Davis, Chap. 6.
Week 7: Change of basis and singular value decomposition
Davis, Chap. 7
Part III. Probability
Week 8: Introduction. Independence. Bayes's Law. Discrete random variables.
Davis, Chap. 8
Week 9+10: Numerical random variables. Expected value and variance.
Davis, Chap. 9
Week 11: Markov models.
Davis, Chap. 10.
Week 12: Information theory and entropy.
Davis, Chap. 13.
Confidence intervals. Monte Carlo methods.
Davis, chaps. 11+12.
You may discuss any of the assignments with your classmates (or anyone else)
but all work for all assignments must be
entirely your own. Any sharing or copying of assignments will be
considered cheating. By the rules of the Graduate School of Arts and Science,
I am required to report any incidents of cheating to the department.
My policy is that any incident of cheating will result in the
student getting a grade of F for the course.
The second incident, by GSAS rules, will result
in expulsion from the University.