Visa version
Visa
< föregående
Jämför
< föregående
Schedule and course plan
Period 2
| Where and when | Activity | Reading | Examination |
|
Tue 3 Nov 10:15-12:00 M1 |
Lecture 1: Introduction Hedvig Kjellström |
Bishop 1 Bishop 2, use as a math reference all through the course |
|
|
Wed 4 Nov 10.15-12.00 M1 |
Lecture 2: Regression Carl Henrik Ek |
Bishop 6.4 | |
|
Thu 5 Nov 13.15-15.00 M2 |
Lecture 3: Gaussian Processes Carl Henrik Ek |
Bishop 6.4 | |
|
Fri 6 Nov 15.15-17.00 V1 |
Exercise 1: Derivations Carl Henrik Ek |
||
|
Wed 11 Nov 10.15-12.00 V3 |
Lecture 4: Representation Learning Carl Henrik Ek |
Bishop 12.2, 12.4 | |
|
Thu 12 Nov 13.15-15.00 L1 |
Lecture 5: Approximative Inference Carl Henrik Ek |
Bishop 6.4.6, 10.1, 10.2 Bishop 10.3, optional |
|
|
Fri 13 Nov 15.15-19.00 V1 |
Exercise 2-3: Variational Bayes Carl Henrik Ek |
||
|
Tue 17 Nov 10.15-12.00 D3 |
Lecture 6: Graphical Models Jens Lagergren |
Bishop 8.1-8.3 | |
|
Wed 18 Nov 10.15-12.00 V22 (small room) |
Lecture 7: Graphical Models contd, Hidden Markov Models Jens Lagergren |
Bishop 13.1, 13.2.1, 13.2.2, 13.2.5, 13.2.6 | |
|
Thu 19 Nov |
Hand-in 12.00 NOON Results on Monday 23 Nov |
Reading, slides from Lectures 2-5 | Assignment 1 |
|
Tue 24 Nov 10.15-12.00 B1 |
Lecture 8: Expectation-Maximization Applied to Hidden Markov Models Jens Lagergren |
Bishop 9.1-9.3 | |
|
Wed 25 Nov 10.15-12.00 E3 |
Lecture 9: Expectation-Maximization contd Jens Lagergren |
||
|
Thu 26 Nov 13.15-15.00 B3 |
Exercise 4: Lectures 6-9 Jens Lagergren |
||
|
Fri 27 Nov 15.15-17.00 E3 |
Lecture 10: Non-Gaussian and Discrete Latent Variable Models Hedvig Kjellström |
Bishop 8.2.2, 12.4.1 Hyvärinen and Oja |
|
|
Tue 1 Dec 10.15-12.00 M2 |
Lecture 11: Bag of Words, Topic Models Hedvig Kjellström |
Blei and Lafferty |
|
|
Wed 2 Dec 10.15-12.00 K2 |
Exercise 5: Probabilistic Independent Component Analysis Whiteboard photos: 1 2 3 4 5 6 7 Hedvig Kjellström |
Beckmann and Smith, optional |
|
|
Thu 3 Dec 13.15-15.00 L51 (small room) |
Lecture 12: Sampling Hedvig Kjellström Whiteboard photo: 1 |
Bishop 11.1-11.3 Griffiths |
|
|
Fri 4 Dec 15.15-17.00 E3 |
Lecture 13: The Structure of a Scientific Paper Hedvig Kjellström |
Allen Duvenaud et al. |
|
|
Tue 8 Dec 12.00-13.00 Room 1448, Lindstedtsv 3 floor 4 |
Help session about Assignment 2, Task 2.1-2.4 Jens Lagergren |
||
|
Tue 15 Dec 10.15-12.00 K2 |
Exercise 6: State-of-the-Art in Machine Learning Hedvig Kjellström |
||
| Wed 16 Dec |
Hand-in 12.00 NOON Results on Wednesday 23 Dec |
Reading, slides from Lectures 6-12 | Assignment 2 |
|
Mon 18 Jan 14.00-18.00 E52 (small room) |
Hand-in 12.00 NOON Oral project presentations, 10 min per project group. Presence is only needed in the 2h session when your group presents. You are allowed to attend the other session if there is space left in the room. Give slides to Hedvig on a stick before the start of the session. Very strict time deadlines! Session 1 14.10 Group 16 14.20 Group 14 14.30 Group 12 14.40 Group 10 14.50 Group 8 15.00 Group 6 15.10 Group 4 15.20 Group 2 15.30 Henrik Talborn 15.40 Yavor Kovachev 15.50 Ramón Heberto Martinez Mayorquin Session 2 16.10 Group 17 16.20 Group 15 16.30 Group 13 16.40 Group 11 16.50 Group 9 17.00 Group 7 17.10 Group 5 17.20 Group 3 17.30 Group 1 17.40 Hanwei Wu |
Paper, slides from Lecture 13 |
Project |
