Course Syllabus: MATH 271B, Winter 2025
Instruction
- Instructor: Jiawang Nie
- Office: AP&M 5864.
- Phone: (858) 534-6015.
- Email: njw "AT" math . ucsd . edu.
- Office hours: 3:00pm-4:00pm (Wednesdays & Fridays, in office).
Lectures
- Time: 3:30pm -4:50pm on TuTh.
- Location: APM 2402.
TA Contact Info
-
We do not have TA at moment.
Course Description
-
This graduate level course will focus on basic theory and methods
in numerical optimization. The topics to be convered include:
unconstrained optimization and optimality conditions,
gradient and Newton methods, quasi-Newton methods,
constrained optimization, Karush-Kuhn-Tucker conditions,
linear and quadratic programming; interior methods;
penalty and barrier function methods; basic duality theory.
-
Prerequisite
- Basic training in real analysis and linear algebra, or consent by the instructor.
Textbook
- There are no required textbooks. The recommended ones are:
Nonlinear Programming by Dimitri Bertsekas;
Numerical Optimization by Jorge Nocedal and Stephen Wright;
Practical Optimization by Philip Gill, Walter Murray and Margaret Wright.
Assignments
-
Homework will be assigned regularly.
Details about completing homework will be given in class.
Please write your names, ID nubmers, and section numbers on your homework.
Exams
-
There is no final exam scheduled for this course.
Grading
-
The grade will be based on the performance
of completing homework assignments and attendance to lectures.
Academic Integrity
-
Every student is expected to conduct themselves with academic integrity.
Any kind of cheatings is not allowed in this course.
Violations of academic integrity will be treated seriously.
-
See
UCSD Policy on Integrity of Scholarship.