課程資訊
課程名稱
Advanced Algorithms 
開課學期
109-2 
授課對象
電機資訊學院  生物資訊學國際研究生學位學程  
授課教師
LU,TZU PIN 
課號
TIGPBP8009 
課程識別碼
947ED0110 
班次
 
學分
3.0 
全/半年
半年 
必/選修
必修 
上課時間
星期五7,8,9(14:20~17:20) 
備註
限博士班 且 限本系所學生(含輔系、雙修生)
總人數上限:20人 
 
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課程概述

Place: Room 107, New Building of the Institute of Information Science, Academia Sinica.
Time: Friday 14:00-17:00
Chair: Dr. Ting-Yi Sung
Aim:
Outline: This course is basically about data mining, machine learning and statistical modeling from data, and some other algorithms and applications.

References: (reserved in the library of the Institute of Information Science)
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/ )

TA: Chun-Yi Chen (陳存儀) Email: chunyichen@iis.sinica.edu.tw

Office hours: TBD

Grades: Midterm exam 50%. Final exam 50%.
Week Date Topics/Brief Description Subtopics/Detail Descriptions/Examples Lecturers
1 2018/02/23 Databases: An Overview N/A Dr. Chih-Ya Shen
2 2018/03/02 Introduction to Data Mining N/A Dr. Chih-Ya Shen
3 2018/03/09 Data Classification: Overview N/A TBD
4 2018/03/16 Standard Optimization Algorithms The outline of the optimization couse: basic idea of optimization, convex optimization, lagrangial method for optimization method, and gradient descent methods. Dr. Wen-Liang Hwang
5 2018/03/23
Support Vector Machines and Large Margin The outline of support vector machine: basic principles for maching learning, the support vector machine is a convex optimization method. So, I can use the results of week 1 in week 2. Dr. Wen-Liang Hwang
6 2018/03/30
Kernel Methods N/A Dr. Wen-Liang Hwang
7 2018/04/06 Nonstandard Optimization Algorithms (GA, Random Forest, and others) N/A Dr. Huai-Kuang Tsai
8 2018/03/13 Review Week
9 2018/04/20 Midterm Exam
10
2018/04/27 Hidden Markov Models (I) N/A Dr. Yu Tsao
11 2018/05/04 Hidden Markov Models (II) N/A Dr. Yu Tsao
12 2018/05/11 Graphical Models (I) N/A Dr. Hsing-Kuo Pao
13 2018/05/18 Graphical Models (II) N/A Dr. Hsing-Kuo Pao
14 2018/05/25 Conditional Random Fields N/A Dr. Richard Tzong-Han Tsai
15 2018/06/01 MapReduce in Cloud Computing N/A Dr. Yu-Rong Chang
16 2018/06/08 Network Analysis N/A Dr. Huan-Cheng Hwang
17 2018/06/15 Review Week
18 2018/06/22 Final Exam 

課程目標
 
課程要求
 
預期每週課後學習時數
 
Office Hours
 
指定閱讀
 
參考書目