Statistical Learning Theory


09810CS 565300 -- Autumn 2009

Tuesday 13:10-15:00 & Thursday 13:10-14:00
234 CS Building


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[2010/1/11]Term project presentation: EECS B1, January 14, Thursday 12:30-14:00.


[2010/1/4] Prof. Tyng-Luh Liu's lecture notes on Boosting, Decision Trees, and Random Forests.


[2009/12/24] Assignment 6 is out: ps6.zip. The name of the pdf file should be ps6_YourStudentID, e.g., "ps6_9762578.pdf". This assignment is due Wednesday, December 30, at 11:59pm.


[2009/12/18] Lecture notes for week 14: SLT09_Week14.pdf.

[2009/12/15] Lecture notes for week 13: SLT09_Week13.pdf.


[2009/12/8] Solutions for the midterm exam.

[2009/12/8] Assignment 5 is out: ps5.zip. The name of the pdf file should be ps5_YourStudentID, e.g., "ps5_9762578.pdf". This assignment is due Wednesday, December 16, at 11:59pm.


[2009/12/5] Lecture notes for week 12: SLT09_Week12.pdf.
[2009/12/4] Solutions of PS1-PS4 collected by the TA and his comments: sol.zip.

[2009/11/29] Lecture notes for week 11: SLT09_Week11.pdf.
[2009/11/26] Lecture notes for weeks 9 & 10: SLT09_Week09.pdf and SLT09_Week10.pdf.

[2009/11/14] Assignment 4 is out: ps4.zip. The name of the pdf file should be ps4_YourStudentID, e.g., "ps4_9762578.pdf". This assignment is due Monday, November 23, at 11:59pm.

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Staff
Instructor: Hwann-Tzong Chen
740 CS Building

Office hours: by appointment, or just stop by
Teaching Assistant:
謝宏坤 g9762578 [at] oz.nthu.edu.tw
綜二館 735 室
Phone: 03-574-2803

Overview

Grading

Assignments (50%): There will be ten assignments, including writing code, running packages, and solving problems. You need to do the programming assignments using MATLAB and C/C++.
Midterm Exam (20%):
Term project (30%): The term project may be done in teams of up to three people.

Textbook

Pattern Recognition and Machine Learning (PRML), Christopher M. Bihsop.

Prerequisites

Students are expected to have general programming experience in Matlab and C/C++. Familiarity with the basic concepts of probability, linear algebra, and calculus is assumed.

Useful links and tools

Resource
Professor Jang's MATLAB tutorial.