E0 299: Computational Linear Algebra
Announcements:
The first meeting is on August 8 at 11:30 am in B-308 (EE department).
The lecture will be for 2 hours (11:00am to 1:00pm) from August 22 to September 26.
Problem sets and solution keys will be posted on Piazza.
The first test will be on September 24 from 11am - 12:30pm.
The second test will be on October 26 from 4:00pm - 5:30pm.
Starting October 10, the lecture will be from 11:00am to 12:30pm.
Starting October 29, the lecture will be from 11:00am to 1:00pm.
The third and final test will be on November 17 from 3:00pm - 4:30pm.
The final exam is on December 5 from 9am - 12pm.
The final lecture is on Nov 21.
Course Details
Term: August - December 2019.
Credits: 3:1.
Webpage: tiny.cc/CLA2019.
Hours: Tuesday and Thursday (11:00 - 12:30 hrs).
Venue: B-308.
Instructor: Kunal N. Chaudhury (kunal@iisc.ac.in).
Teaching Assistants: Pravin, Haritha, Amal.
Grading: math problems (15%), coding assignments (15%), tests (20%), final exam (50%).
Objective: To provide a good mix of geometric intuition, theorem proving, and how things can be computed efficiently. This is really an introductory course on linear algebra with a focus on theory, but we will also touch upon some algorithmic aspects without getting into details (coding assignments will be given in this regard).
Syllabus:
Theory: Solution of linear equations, vector space, linear transformation, matrix representation, inner-products and norms, orthogonality, least squares, trace and determinant, eigendecomposition, symmetric (Hermitian) matrices and quadratic forms, singular value decomposition, and applications.
Computations: Gaussian elimination, iterative methods, QR decomposition, eigenvalues, power method, QR algorithm.
Textbooks:
S. Axler, Linear Algebra Done Right, Springer, 2015.
G. Strang, Linear Algebra and its Applications, Wellesley-Cambridge Press, 2016.
L. Trefethen and D. Bau, Numerical Linear Algebra, SIAM, 1997.
Web resources:
http://ocw.mit.edu/18-06S05 (video lectures by Strang)
http://linear.axler.net/LinearAbridged.pdf (abridged textbook)
http://vmls-book.stanford.edu/ (applications of linear algebra)
http://immersivemath.com/ila/index.html (has nice visualizations)
https://math.stackexchange.com/?tags=linear-algebra (lots of Q/A)