2025-26 Spring
IOTA5502 · L01
CUI, Ying
3 Credits · Class #6110 · Reference Capacity 20
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Convex and Nonconvex Optimization II
Information Hub / Internet of Things · 3 Credits
This course covers advanced theory, algorithms, and applications for convex and nonconvex optimization, including: subgradient methods, localization methods, decomposition methods, proximal methods, alternating direction methods of multipliers, conjugate direction methods, successive approximation methods, convex-cardinality problems, low-rank optimization problems, neural networks, semidefinite programming and relaxation, robust optimization, discrete optimization, stochastic optimization, etc.
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3 Credits
官方数据更新时间: 2026-08-06 14:55:26
背景: Good knowledge of calculus, linear algebra, and fundamental optimization theory and algorithms, and exposure to probability. Exposure to communications, signal processing, automatic control, and machine learning is helpful but not required. Capable of reading and dissecting scientific papers.
3 Credits
官方数据更新时间: 2026-08-28 05:35:00
背景: Good knowledge of calculus, linear algebra, and fundamental optimization theory and algorithms, and exposure to probability. Exposure to communications, signal processing, automatic control, and machine learning is helpful but not required. Capable of reading and dissecting scientific papers.
3 Credits
官方数据更新时间: 2026-08-06 14:55:26
背景: Good knowledge of calculus, linear algebra, and fundamental optimization theory and algorithms, and exposure to probability. Exposure to communications, signal processing, automatic control, and machine learning is helpful but not required. Capable of reading and dissecting scientific papers.
3 Credits
官方数据更新时间: 2026-08-06 14:55:26
背景: Good knowledge of calculus, linear algebra, and fundamental optimization theory and algorithms, and exposure to probability. Exposure to communications, signal processing, automatic control, and machine learning is helpful but not required. Capable of reading and dissecting scientific papers.
3 Credits
官方数据更新时间: 2026-08-06 14:55:26
背景: Good knowledge of calculus, linear algebra, and fundamental optimization theory and algorithms, and exposure to probability. Exposure to communications, signal processing, automatic control, and machine learning is helpful but not required. Capable of reading and dissecting scientific papers.
3 Credits
官方数据更新时间: 2026-08-06 14:55:26
背景: Good knowledge of calculus, linear algebra, and fundamental optimization theory and algorithms, and exposure to probability. Exposure to communications, signal processing, automatic control, and machine learning is helpful but not required. Capable of reading and dissecting scientific papers.
3 Credits
官方数据更新时间: 2026-08-06 14:55:26
背景: Good knowledge of calculus, linear algebra, and fundamental optimization theory and algorithms, and exposure to probability. Exposure to communications, signal processing, automatic control, and machine learning is helpful but not required. Capable of reading and dissecting scientific papers.
3 Credits
官方数据更新时间: 2026-08-06 14:55:26
背景: Good knowledge of calculus, linear algebra, and fundamental optimization theory and algorithms, and exposure to probability. Exposure to communications, signal processing, automatic control, and machine learning is helpful but not required. Capable of reading and dissecting scientific papers.