Math 273C: Numerical Optimizatoin

  • Instructor: Wotao Yin

  • Lecture: Monday, Wednesday, Friday 2-2:50pm in MS 7608

  • Prerequisites: calculus, numerical linear algebra, and some analysis. Math 273A and 273B are not required.

  • Piazza forum

Textbook

Numerical Optimization, 2nd Edition, by Jorge Nocedal and Stephen Wright

Tentative weekly plan

  1. Week 1: Intro. to constrained and unconstrained optimization; optimality conditions; rate of convergence

  2. Week 2: First-order methods

  3. Week 3: Second-order methods

  4. Week 4: Line search methods

  5. Week 5: Constrained optimization methods

  6. Week 6: Dual and augmented Lagrangian methods

  7. Week 7: Stochastic optimization methods

  8. Week 8: Coordinate update methods

  9. Week 9: Derivative-free optimization methods

  10. Week 10: final project presentation

In addiiton, each Friday lecture will include numerical result using Matlab, C/C, Python, etc.

Policies

  1. Percentage: participation 30% (especially each Friday), homework 40%, final project 30%

  2. Lateness policy: No extension will be granted. No late submission will be accepted. No exceptions.

  3. Homework policy: You are encouraged to discuss homework questions. However, you must write your own solutions. Copying others’ solutions is considered a serious violation, which will be immediately reported. You should never share your written solutions with anyone else. Posting solutions online is a serious violation. There will be bi-weakly homework assignments. Please use word processing software such as Latex to type your solutions. Grading will take both correctness and clarity into consideration. Homework will be submitted during lectures.

Students with disabilities

Students needing an academic accommodation based on a disability should contact the Office for Students with Disabilities (OSD) located at (310) 825-1501 or A255 Murphy Hall. When possible, students should contact the OSD within the first two weeks of the term as reasonable notice is needed to coordinate accommodations. For more information visit www.osd.ucla.edu.


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