Course 419.622: Statistical Learning Theory
(Knowledge Representation and Reasoning)
¼¼¹Ì³ª ÇÑ ¹ßÇ¥ ÆÄ¿öÆ÷ÀÎÆ® ÆÄÀÏÀ»
º¸³»ÁÖ¼¼¿ä.
ÆÄÀÏ À̸§Àº
"¸î¹øÂ°¼¼¹Ì³ª_chapter¹øÈ£.ppt"
ÀÔ´Ï´Ù.
ÅÒ ÇÁ·ÎÁ§Æ® º¸°í¼ÀÇ ÆÄÀÏÀ»
º¸³»ÁÖ¼¼¿ä.
ÆÄÀÏÀ̸§Àº
"Çйø.???"
ÀÔ´Ï´Ù.
À§ ¸ÞÀÏÀ» º¸³»½Ç ¶§ ¸ÞÀÏÀÇ Á¦¸ñÀº
"Áö½ÄÇ¥Çö ¹× Ãß·Ð_À̸§_Çйø_ÅÒÇÁ·ÎÁ§Æ®Á¦¸ñ"
À¸·Î ÇØ ÁÖ¼¼¿ä.
´Ù¸¥ »ç¶÷µéÀÌ ¾î¶² ÇÁ·ÎÁ§Æ®¸¦ Çß´ÂÁö º¼ ¼ö ÀÖ½À´Ï´Ù.
Term Project Reports
Department of Computer Engineering, Seoul National University
Instructor
: Prof. Byoung-Tak Zhang
TA
: Jong-Woo Lee (
E-mail
, Tel.: 880-7302)
Classroom
: 301-101
Time
: Wed 3-4pm and Fri 3-5pm
Text
:
Learning from Data: Concepts, Theory, and Methods
, V. Cherkassky and F. Mulier, Wiley, 1998.
Supplement 1
:
Data Mining with Neural Networks
, J. P. Bigus (Ed.), McGraw-Hill, 1996.
Supplement 2
:
Predictive Data Mining
, S. M. Weiss and N. Indurkhya (Eds.), Morgan Kaufmann, 1998.
Supplement 3
:
Machine Learning and Data Mining: Methods and Applications
, R. S. Michalski, I. Bratko, and M. Kubat (Eds.), Wiley, 1998.
Requirements
:
Two open-book exams, a paper presentation, and a term project
Schedule
Week 1: Introduction (Chap 1)
[slides]
Week 2: Classical Approaches and Adaptive Learning (Chap 2)
[slides]
Week 3:
Data Mining Seminar 1
Week 4:
Data Mining Seminar 2
Week 5: Regularization Framework (Chap 3)
[slides]
Week 6: Statistical Learning Theory (Chap 4)
[slides]
Week 7: Nonlinear Optimization Strategies (Chap 5)
[slides]
Week 8: Data/Dimensionality Reduction (Chap 6)
[slides]
Week 9: Midterm Exam
Week 10:
Data Mining Seminar 3
Week 11:
Data Mining Seminar 4
Week 12: Regression (Chap 7)
[slides]
Week 13: Classification (Chap 8)
[slides]
Week 14: Support Vector Machines (Chap 9)
[slides]
Week 15: Presentations of Term Projects
Week 16: Final Exam
½½¶óÀ̵å´Â Acrobat4.0¿¡¼ º¸½Ç¼ö ÀÖ½À´Ï´Ù.
Term Project Reports
Back to [
AI Lab (SCAI)
] [
Zhang's Home Page
] [
Dept. of Computer Eng.
]