週次 |
日期 |
單元主題 |
第1週 |
3/04 |
Lecturer: Frederick Kin Hing Phoa (潘建興)
Lecture 01: Introduction to Metaheuristics Optimization
Lecture 02: Genetic Algorithm #1: Introduction and Concepts
Lecture 03: Genetic Algorithm #2: Algorithm, Programming and Practice |
第2週 |
3/11 |
Lecturer: Frederick Kin Hing Phoa (潘建興)
Lecture 04: Stochastic Optimization: Introduction and Concepts
Lecture 05: Simulated Annealing #1: Introduction and Concepts
Lecture 06: Simulated Annealing #2: Algorithm, Programming and Practice |
第3週 |
3/18 |
Lecturer: Frederick Kin Hing Phoa (潘建興)
Lecture 07: Particle Swarm Optimization #1: Introduction and Concepts
Lecture 08: Particle Swarm Optimization #2: Algorithm, Programming and Practice
Lecture 09: Particle Swarm Optimization #3: Improvement and Parallel Computing |
第4週 |
3/25 |
Lecturer: Frederick Kin Hing Phoa (潘建興)
Lecture 10: Ant Colony Optimization #1: Introduction and Concepts
Lecture 11: Ant Colony Optimization #2: Algorithm, Programming and Practice
Lecture 12: Fuzzy System Optimization: Introduction, Algorithm and Practice |
第5週 |
4/01 |
Lecturer: Frederick Kin Hing Phoa (潘建興)
Lecture 13: Advanced Topic #1: Optimization in Neural Networks
Lecture 14: Advanced Topic #2: Recent Advances in Swarm Intelligence
Lecture 15: Advanced Topic #3: Improvement of Metaheuristics via Quantum Mechanics |
第6週 |
4/08 |
Lecturer: Shwu-Rong Grace Shieh (謝叔蓉)
Lecture 1: Introduction and Principle component analysis
Lecture 2: Principle component analysis
Lecture 3: Applications to biomedical data/Data for projects |
第7週 |
4/15 |
Lecturer: Shwu-Rong Grace Shieh (謝叔蓉)
Lecture 1: Introduction of Data for your projects
Lecture 2: Modeling (Regularized regression, lasso, ridge, etc)
Lecture 3: Applications to biomedical data |
第9週 |
4/29 |
Lecturer: Shwu-Rong Grace Shieh (謝叔蓉)
Lecture 1: Introduction
Lecture 2: Methods for classification (k-Nearest neighbor, etc)
Lecture 3: Applications to precision medicine |
第10週 |
5/06 |
Lecturer: Shwu-Rong Grace Shieh (謝叔蓉)
Lecture 1: Students' presentation (5 min. to present your or group's initial ideas for the project)
Lecture 2: Students' presentation
Lecture 3: Students' presentation |
第11週 |
5/13 |
Lecturer: Tso-Jung Yen (顏佐榕)
Matrix differentiation |
第12週 |
5/20 |
Lecturer: Tso-Jung Yen (顏佐榕)
Convex analysis and convex optimization |
第13週 |
5/27 |
Lecturer: Tso-Jung Yen (顏佐榕)
Alternating direction methods of multipliers |
第14週 |
6/03 |
Lecturer: Tso-Jung Yen (顏佐榕)
proximal algorithms |
第15週 |
6/10 |
Lecturer: Tso-Jung Yen (顏佐榕)
Deep learning and stochastic gradient algorithms |