數值最佳化與應用
Numerical Optimization with applications
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3 10:10–11:00 | 數值最佳化與應用 SA215（光復） 2 節連堂 | |
4 11:10–12:00 | ||
6 14:20–15:10 | 數值最佳化與應用 SA215（光復） |
* 根據陽明交大上課時間表所列
This course is about how to numerically solve optimization problems. When you try to minimize the energy in a physical system, train a machine learning model, or optimize a design, numerical optimization plays an important role. In this course, we will start with the basic methods such as gradient descent and Newton’s method—and work our way up to powerful techniques like quasi-Newton methods and interior-point algorithms. The focus is on understanding how and why these methods work, and also when to use which method. You will get hands-on experience implementing algorithms, analyzing their performance, and applying them to real-world problems.
Calculus、Linear Algebra and Computational mathematics
無備註
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Homework 20% Exams 80%
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Numerical Optimization, 2nd Edition, Jorge Nocedal & Stephen J. Wright
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