週次 |
日期 |
單元主題 |
第1週 |
9/16 |
Lecturer: Frederick Kin Hing Phoa (潘建興)
Lecture 1:
01-1 Introduction to Optimization
01-2 Metaheuristic Optimization: An Introduction
01-3 Traditional Methods: Random Sampling, Hill Climbing, Random Walk |
第2週 |
9/23 |
Lecturer: Frederick Kin Hing Phoa (潘建興)
Lecture 2:
02-1 Simulated Annealing: Metropolis Algorithm, Temperature Schedule
02-2 Tabu Search: Introduction, Iterated Local Search
02-3 Comparison between Optimization Algorithms |
第3週 |
9/30 |
Lecturer: Frederick Kin Hing Phoa (潘建興)
Lecture 3:
03-1 Genetic Algorithm I: Fundamental Idea and Hypothesis
03-2 Genetic Algorithm II: Selection, Crossover, Mutation
03-3 Genetic Algorithm III: Schema Theorem |
第4週 |
10/07 |
Lecturer: Frederick Kin Hing Phoa (潘建興)
Lecture 4:
04-1 Particle Swarm Optimization I: Basic Phenomena
04-2 Particle Swarm Optimization II: Algorithm
04-3 Particle Swarm Optimization III: Parallel Computing |
第5週 |
10/14 |
Lecturer: Frederick Kin Hing Phoa (潘建興)
Lecture 5:
05-1 Ant Colony Optimization I: Basic Phenomena
05-2 Ant Colony Optimization II: Algorithm
05-3 Memetic Algorithm: Basic Introduction |
第6週 |
10/21 |
Lecturer: Frederick Kin Hing Phoa (潘建興)
Lecture 6:
06-1 Advanced Topic I: Difficulties in Optimization
06-2 Advanced Topic II: Evolution Strategies
06-3 Final Project: A Discussion |
第7週 |
10/28 |
Lecturer: Shwu-Rong Grace Shieh (謝叔蓉)
Lecture 1: Introduction of Dimension Reduction
Lecture 2: Principal component analysis
Lecture 3: Applications to biomedical data |
第8週 |
11/04 |
Lecturer: Shwu-Rong Grace Shieh (謝叔蓉)
Theme: Modeling high-dimensional data
Lecture 1: Introduction of Data for your projects
Lecture 2: Modeling with variable selection (lasso, ridge, etc)
Lecture 3: Applications to drug response prediction |
第9週 |
11/11 |
Midterm week (No lecture) |
第10週 |
11/18 |
Lecturer: Shwu-Rong Grace Shieh (謝叔蓉)
Theme: Prediction via machine learning
Lecture 1: Introduction
Lecture 2: k-Nearest neighbor
Lecture 3: Applications to drug response data
|
第11週 |
11/25 |
Lecturer: Shwu-Rong Grace Shieh (謝叔蓉)
Theme: Prediction via machine learning
Lecture 1: Introduction
Lecture 2: Method: Support Vector Machines
Lecture 3: Applications to precision medicine
|
第12週 |
12/02 |
Lecturer: Shwu-Rong Grace Shieh (謝叔蓉)
Lecture 1: Students' presentation (5 min. to present your initial ideas for the project)
Lecture 2: Students' presentation
Lecture 3: Students' presentation |
第13週 |
12/09 |
Lecturer: Tso-Jung Yen (顏佐榕)
Matrix computation |
第14週 |
12/16 |
Lecturer: Tso-Jung Yen (顏佐榕)
Convex optimization I |
第15週 |
12/23 |
Lecturer: Tso-Jung Yen (顏佐榕)
Convex optimization II |
第16週 |
12/30 |
Lecturer: Tso-Jung Yen (顏佐榕)
Convex optimization III |
第17週 |
1/06 |
Lecturer: Tso-Jung Yen (顏佐榕)
Algorithms in deep learning |