일시 | Chapter | 발표자 | 발표자료 |
2016-05-27 | 1. Introduction and Overview (week 1) Bayesian Network Fundamentals (week1) |
김보섭 | 발표자료 |
2016-06-03 | 2. Template Models (week1) | 조수현 | 발표자료 |
2016-06-10 | 3. Structured CPDS (week2) | 류나현 | 발표자료 |
2016-06-29 | 4. Markov Network Fundamentals (week2) | 류나현 | 발표자료 |
2016-07-05 | 5. Representation Wrapup : Knowledge Engineering (week 3) Inference : Variable Elmination (week 3) |
박민식 | 발표자료 |
2016-07-12 | 6. Inference : Belief Propagation, Part 1 (week 3) Inference : Belief Propagation, Part 2 (week 4) |
김형석 | 발표자료 |
2016-07-26 | 7. Inference : MAP Estimation, Part 1 (week 4) Inference : MAP Estimation, Part 2 (week 5) |
박재선 | 발표자료 |
2016-08-02 | 8. Inference : Sampling Methods (week 5) Inference : Temporal Models and Wrap-up (week 6) |
서덕성 | 발표자료 |
2016-08-10 | 9. Decision Theory (week 6) ML-class Revision (week 6) |
김준홍 | 발표자료 |
2016-08-17 | 10. Learning: Overview (week 6) Learning : Parameter Estimation in BNs (week 7) Learning : Parameter Estimation in MNs (week 7) |
김해동 | 발표자료 |
2016-08-24 | 11. Structure Learning (week 8) | 조수현 | 발표자료 |
2016-09-05 | 12. Learning With Incomplete Data (week 9) | 김보섭 | 발표자료 |