The Elements of Statistical Learning Seminar

Time and Place

Time: Mon. Thu. 3:00, Fri. 7:00
Place: 138 - 415 seminar room

Date Title Speaker
01/23
Mon.
Ch2. Overview of Supervised Learning [down]
I.-H. Lee
K.-I. Kim
01/25
Wed.
Ch3. Linear Methods for Regression [down]
J.-G. Joung
S.-.J Kim
02/02
Thu.
Ch4. Linear Methods for Classification [down]
S.-Y. Shin
02/06
Mon.
Ch5. Basis Expansions and Regularization [down]
S. Kim
J.-K. Kim
02/08
Wed.
Ch6. Kernel Methods [down]
J.-K. Rhee
02/10
Fri.
Ch7. Model Assessment and Selection [down]
J.-W. Nam
02/13
Mon.
Ch8. Model Inference and Averaging [down]
Y.-K. Roh
B.-H. Kim

02/17
Fri.

Ch9. Additive Models, Trees, and Related Methods [down]
I.-H. Lee
02/20
Mon.
Ch10. Boosting and Additive Trees [down]
J.-G. Joung
02/20
Mon.
Ch11. Neural Networks [down]
S.-Y. Shin
02/22
Wed.
Ch12. Support Vector Machines and Flexible Discriminants [down]
M.-O. Heo
02/24
Fri.
Ch13. Prototype Methods and Nearest-Neighbors [down]
J.-H. Eom
02/27
Mon.
Ch14. Unsupervised Learning [down]
S. Kim
B.-H. Kim


This page is maintained by Soo-Jin Kim(sjkim@bi.snu.ac.kr)
Last update: 2006-02-16
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