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CSE 5403

Algorithms for Nonlinear Optimization

COMPUTER SCIENCE AND ENGINEERING

The course will provide an in-depth coverage of modern algorithms for the numerical solution of multidimensional optimization problems. Unconstrained optimization techniques including Gradient methods, Newton's methods, Quasi-Newton methods, and conjugate methods will be introduced. The emphasis is on constrained optimization techniques: Lagrange theory, Lagrangian methods, penalty methods, sequential quadratic programming, primal-dual methods, duality theory, nondifferentiable dual methods, and decomposition methods. The course will also discuss applications in engineering systems and use of state-of-the-art computer codes. Special topics may include large-scale systems, parallel optimization, and convex optimization. Prerequisites: Calculus I and Math 309

Instructors

Chen, Yixin Chen

3.0
Quality
1.6
Difficulty
5
Reviews
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Reviews

Quality: 1Difficulty: 1Chen

Although Chen is a decent lecturer, his class design is awful. You'd learn more about the topic in the first three weeks of the electrical engineering undergrad course. Chen lectured around 6 times and the rest were peer presentations (he doesn't even attend these himself) with no in-depth content. Insanely easy A but don't expect to learn.

6/17/2023

Quality: 2Difficulty: 1Chen

This class is ridiculously easy compared to any 500-level class, especially a Theory class. His lectures are very clear, but it only lasts for a month, and the rest are presentations and a group project, which are all graded uniformly.

10/16/2022

Quality: 5Difficulty: 3Chen

He is very knowledgeable about the topic, right to the point. dunno about others, but this course has the right difficulty for me who just want to know more about optimization but don't like too much math. the course presentations by peers are awesome as they cover some current applications in machine learning, which I am eager to learn about

12/6/2020

Quality: 2Difficulty: 1Chen

Prof Chen is going to offer about 10 lectures and skip the rest of the semester. So you basically just going to listen to peer's lectures, which has various quality.

6/30/2019

Quality: 5Difficulty: 2Chen

Chen is an expert in optimization. What I liked most is the organization of the course: a mixture of classical stuff and modern applications. He would condense a 400 page textbook in to a series of insightful slides and pick out the key concepts for us. Oh, you don't need to be a math genius to pass this course.

11/1/2018