高等演算法
Advanced Algorithm
| 節 | 週五 |
|---|---|
6 14:20–15:10 | 高等演算法 3 節連堂 |
7 15:30–16:20 | |
8 16:30–17:20 |
* 根據陽明交大上課時間表所列
This course is basically about data mining, machine learning and statistical modeling from data, and some other algorithms and applications.
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Midterm exam 50%. Final exam 50%.
Sequence analysis algorithms
Machine Learning
High-throughput Data Analysis
| 週次 | 主題 |
|---|---|
| 第 1 週 | Databases: An Overview 2/17 |
| 第 2 週 | Introduction to Data Mining 2/24 |
| 第 3 週 | Data Classification: Overview 3/3 |
| 第 4 週 | Standard Optimization Algorithms 3/10 |
| 第 5 週 | Support Vector Machines and Large Margin 3/17 |
| 第 6 週 | Kernel Methods 3/24 |
| 第 7 週 | Nonstandard Optimization Algorithms (GA, Random Forest, and others) 3/31 |
| 第 8 週 | Review Week 4/7 |
| 第 9 週 | Midterm Exam 4/14 |
| 第 10 週 | Hidden Markov Models (I) 4/21 |
| 第 11 週 | Hidden Markov Models (II) 4/28 |
| 第 12 週 | Graphical Models (I) 5/5 |
| 第 13 週 | Graphical Models (II) 5/12 |
| 第 14 週 | Conditional Random Fields 5/19 |
| 第 15 週 | MapReduce in Cloud Computing 5/26 |
| 第 16 週 | Network Analysis 6/2 |
| 第 17 週 | Review Week 6/9 |
| 第 18 週 | Final Exam 6/16 |
1. First Course in Database Systems (3rd Edition, Ullman and Widom, 2007) 2. Learning from Data- A Short Course (Abu-Mostafa, Magdon-Ismail, Lin, 2012) 3. Learning Pattern Classification (Duda, Harg, and Stork, 2001) 4. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods (Cristianini and Shawe-Taylor, 2000) 5. Convex optimization (Boyd and Vandenberghe, 2004; book and lecture slides available at http://www.stanford.edu/~boyd/cvxbook/ )
- 地點
- Institute of Information Science, Academia Sinica
- 時間
- by appointment
- 聯絡方式
- by email