Optimization
Lecture, three hours; discussion, one hour. Enforced requisites: courses 115A, 131A. Not open for credit to students with credit for former Electrical Engineering 136. Fundamentals of optimization. Linear programming: basic solutions, simplex method, duality theory. Unconstrained optimization, Newton method for minimization. Nonlinear programming, optimality conditions for constrained problems. Additional topics from linear and nonlinear programming. P/NP or letter grading.
Review Summary
- Clarity
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10.0 / 10
- Organization
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10.0 / 10
- Time
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5-10 hrs/week
- Overall
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10.0 / 10
Enrollment Progress
Section List
LEC 2
Open (2 seats)MWF 12pm-12:50pm
Mathematical Sciences 5137
LEC 3
Open (2 seats)MWF 3pm-3:50pm
Mathematical Sciences 5137
Reviews
Professor Meng is very experienced in the field of convex optimization; her lectures can be a bit technical but they do present concepts and algorithms in an organized way. Her exams are very challenging and she does not curve. However, if you put some work into the class and really understand how things work, they should be fine. By the way, Professor Meng is very friendly and always willing to help during office hours. Overall I would recommend the class for the academic depth and challenge it offers.
Professor Meng is the goat, talks about a lot of content in class, with a heavy focus on algorithm, but her lecture is clear and inspiring. The content you learnt in this class will be of great help if you are going into machine learning.
Very helpful professor even if it was a somewhat challenging class! I was surprised at how well I was able to do.
Displaying all 3 reviews
Course
Grading Information
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No group projects
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Attendance not required
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1 midterm
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Finals week final
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100% recommend the textbook
Previous Grades
Grade distributions not available.