CSE 291, Fall 2015 Topics on Scientific Computation

University of California, San Diego

Instructor

• CK Cheng, ckcheng+291@ucsd.edu, 858 534-6184

Schedule

• Lectures: 5-620PM TTH, Room WLH2113

References

• Convex Optimization, S. Boyd and L. Vandenberghe, Cambridge, 2004 (required textbook).
• Numerical Recipes: The Art of Scientific Computing, Third Edition, W.H. Press, S.A. Teukolsky, W.T. Vetterling, and B.P. Flannery, Cambridge University Press, 2007.
• Funcions of Matrices: Theory and Computation, N.J. Higham, SIAM, 2008.
• Fall 2015, Convex Optimization by R. Tibshirani, http://www.stat.cmu.edu/~ryantibs/convexopt/
• EE364a: Convex Optimization I, S. Boyd, http://stanford.edu/class/ee364a/

Prerequisite

Basic knowledge of numerical methods or intention of conducting projects related to scientific computation.

Assignment and Grading

Grading is based on class participation, 6 to 8 homeworks and a project with final presentation.

Content

We survey modern scientific computation methods. We will start with reviews of the necessary background. The emphasis is on solving large complex problems using low complexity approaches.

Extra Materials

• Conjugate Gradient Tutorial by CK Cheng.
• Nesterov Method: Differential Equation by Su, Boyd and Candes.
• Nesterov Method: Gradient and Mirror Descent by Zhu and Orecchia.

Exercises from Convex Optimization by Boyd and Vandenberghe, additional exercises (Ax.x) and data files: http://stanford.edu/~boyd/cvxbook/

• Exercise 1: Due 10/1/2015: 2.8, 2.10, 2.12, 2.24a, 2.25, and 2.31.
• Exercise 2: Due 10/8/2015: 3.1, 3.8, 3.14, 3.16, 3.22, and 3.36.
• Exercise 3: Due 10/15/2015: 4.1, 4.8, 4.11, 4.15, and 4.33ab.
• Exercise 4: Due 10/22/2015: 5.1, 5.18, 5.22, 5.26, 5.31 and A3.3.
• Exercise 5: Due 10/29/2015: 9.2, 9.6, 9.9, 9.23, and 9.30+A8.3.
• Exercise 6: Due 11/5/2015: 10.1, 10.6, 10.10, 10.15 and 10.16.

Project

• Outlines (title, motivation, statement of the problem, wish list, references) due 11/17/2015.