高等演算法
Advanced Algorithm
學期
107-2
學分
3
學分
當期課號
5757
永久課號
IBI7009
開課單位
生物資訊及系統生物研究所
授課教師
中研院國際學程
類別
選修
上課時間表
| 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
概述
This course is basically about data mining, machine learning and statistical modeling from data, and some other algorithms and applications.
先修科目
無 (N/A)
評分方式
Midterm exam 50%. Final exam 50%.
課程大綱
- Sequence analysis algorithms
- Machine Learning
- High-throughput Data Analysis
週次計畫
| 週次 | 主題 |
|---|---|
| 第 1 週 | Databases: An Overview |
| 第 2 週 | Introduction to Data Mining |
| 第 3 週 | Data Classification: Overview |
| 第 4 週 | Standard Optimization Algorithms |
| 第 5 週 | Support Vector Machines and Large Margin |
| 第 6 週 | Kernel Methods |
| 第 7 週 | Nonstandard Optimization Algorithms (GA, Random Forest, and others) |
| 第 8 週 | Review Week |
| 第 9 週 | Midterm Exam |
| 第 10 週 | Hidden Markov Models (I) |
| 第 11 週 | Hidden Markov Models (II) |
| 第 12 週 | Graphical Models (I) |
| 第 13 週 | Graphical Models (II) |
| 第 14 週 | Conditional Random Fields |
| 第 15 週 | MapReduce in Cloud Computing |
| 第 16 週 | Network Analysis |
| 第 17 週 | Review Week |
| 第 18 週 | Final Exam |
教科書
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/ )
Office Hours
- 地點
- Institute of Information Science, Academia Sinica
- 時間
- by appointment
- 聯絡方式
- by email