공지사항
| 공지 시작 | |
|---|---|
| 공지 종료 |
|
Lect. |
Date |
Topic |
Reading |
HW |
|
L1 |
2/8, Tue. |
Registration, Introduction |
Chapter 1 |
|
|
L2 |
2/10, Thu. |
ML, Bayesian approach I |
Chapter 2, 3, 4 |
|
|
L3 |
2/15, Tue. |
Bayesian approach II |
Chapter 2, 3, 4 |
|
|
L4 |
2/17, Thu. |
Decision Theory I |
Chapter 2, 3, 4 |
|
|
L5 |
2/22, Tue. |
Non-parametric Methods |
Chapter 2 |
|
|
L6 |
2/24, Thu. |
EM |
Chapter 8 |
HW1 out |
|
-- |
3/1, Tue. |
No class(Samiljeol) |
-- |
|
|
L7 |
3/3, Thu. |
Graphical Model I |
Chapter 8 |
|
|
L8 |
3/8, Tue. |
Graphical Model lI |
Chapter 8 |
|
|
L9 |
3/10, Thu. |
Graphical Model IlI |
Chapter 8 |
HW1 due, HW2 out |
|
L10 |
3/15, Tue. |
Regression l |
Chapter 3 |
|
|
L11 |
3/17, Thu. |
Regression ll |
Chapter 3 |
|
|
L12 |
3/22, Tue. |
Linear Classifiers |
Chapter 4 |
|
|
L13 |
3/24, Thu. |
Large-margin Classifier |
Chapter 6, 7 |
HW2 due |
|
-- |
3/29, Tue. |
No Class(Midterm exam week) |
-- |
|
|
-- |
3/31, Thu. |
No Class(Midterm exam week) |
-- |
|
|
L14 |
4/5, Tue. |
Perceptron & Neural Network |
Chapter 4 |
|
|
L15 |
4/7, Thu. |
Kernel Classifiers I |
Chapter 6, 7 |
|
|
L16 |
4/12, Tue. |
Kernel Classifiers II |
Chapter 6, 7 |
|
|
L17 |
4/14, Thu. |
Model selection I |
Chapter 3, 7 |
|
|
L18 |
4/19, Tue. |
Model selection II: Generalization bounds, VC dimensions |
Chapter 3, 7 |
HW3 out |
|
L19 |
4/21, Thu. |
Nearest Neighbor |
Chapter 2 |
|
|
L20 |
4/26, Tue. |
Tree |
Chapter 8 |
|
|
L21 |
4/28, Thu. |
Boosting l |
Chapter 14 |
|
|
L22 |
5/3, Tue. |
Boosting ll |
Chapter 14 |
HW3 due |
|
-- |
5/5, Thu. |
No Class(Children's day) |
-- |
|
|
-- |
5/10, Tue. |
No Class(Vesak) |
-- |
|
|
L23 |
5/12, Thu. |
Feature Selection |
-- |
HW4 out |
|
L24 |
5/17, Tue. |
Sampling |
Chapter 11 |
|
|
L25 |
5/19, Thu. |
Non-parametric Bayesian approach |
Chapter 6 |
|
|
-- |
5/24, Tue. |
No Class(Final exam week) |
-- |
|
|
-- |
5/26, Thu. |
No Class(Final exam week) |
-- |
HW4 due |
