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

Python Code

Carl Henrik Ek

Bishop 6.4

Thu 5 Nov

13.15-15.00

M2

Lecture 3: Gaussian Processes

Python Code

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

Slides & notes.

Jens Lagergren

Bishop 9.1-9.3

Wed 25 Nov

10.15-12.00

E3

Lecture 9: Expectation-Maximization contd

Jens Lagergren

Slides & notes.

Thu 26 Nov

13.15-15.00

B3

Exercise 4: Lectures 6-9

Jens Lagergren

Training HMMs in more detail

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

Hedvig Kjellström skapade sidan 13 augusti 2015

Lärare Hedvig Kjellström ändrade rättigheterna 14 september 2015

Kan därmed läsas av alla och ändras av lärare.
kommenterade 7 november 2015

Fri 6 Nov: Is one page missing from the derivationsThe last page is numbered 10 but here are only 9 pages. Looking at each one it seems page 3 is missing. Or you skipped a number after page 2...

Lärare kommenterade 7 november 2015

Thank you Kristófer,

I have simply made an error in the numbering, 3 is non-existent.

Cheers,

Carl Henrik

Lärare kommenterade 7 november 2015

Also, I still have not scanned the derivation of the Gaussian marginal which I did not do yesterday in the interest of time and discussion. I do not have access to a scanner right now but will post them as soon as I do.

kommenterade 11 november 2015

Hi Carl!

On slide 106 in lecture 3 (the one about GP) there is an equation for posterior. the mean is k(x_star, X).transpose dot K(X,X)^-1 dot f. But if k(x_star, X) has the size 200 x 7 then I can't really get the matrices' sizes to match... Also according to Wikipadia there is no transpose for this one: k(x_star, X) -> so is transpose a typo or am I missing something here?

Thanks :)

Lärare kommenterade 11 november 2015

Hi, you are not missing something at all, its just all about getting the dimensions to match up, so the dimensions should be this in your multiplications,

[200x7][7x7][7x1] = [200x1] so according to my matrix above the equation, k(x_start,X) has to have dimension 200x7 which means that there should be no transpose.

Sorry about this and hopefully its clear now.

kommenterade 11 november 2015

Thanks :)

kommenterade 12 november 2015

Could you perhaps upload the font demo code from yesterday? Thanks

Lärare kommenterade 12 november 2015

Hi,

The code that I am using for this is a package called GPy which you can download from here https://github.com/SheffieldML/GPy . The model that I am using is a Bayesian GP-LVM model, under models, BGPLVM you can see how to run it. However, I am not allowed to share the data for the fonts as the one who created them wants to keep it to himself. Sorry about that, but you can try some other interesting data inside the GPy package, for example motion capture data.

kommenterade 12 november 2015

I'm a bit curious about the oral assessments mentioned in the schedule, "Selected oral assessments during Friday 20 nov (see Assignments)"

How will this happen? When do you know if you have been selected for one?

Asking here since I can't find anything about it on the assignments page, and I'm not in Sweden at that date..

En användare har tagit bort sin kommentar
En användare har tagit bort sin kommentar
Lärare kommenterade 15 november 2015

We have removed the formulation "selected oral assignments", due to the large number of students we have decided to go over to an entirely text-format examination of the two assignments.

Lärare kommenterade 16 november 2015

Due to (or rather thanks to - it is great!) the large number of students we have had to rebook lecture halls. Please look in the updated schedule on the course web pages, HT 2015 mladv15 > Schedule and cours plan, and take notes of the new rooms, starting Tuesday Nov 24.

We did not get larger rooms for some of the lectures; these are marked with boldface and "(small room)".  These rooms fit around 60 students, which means that we will have to do an ad-hoc solution, e.g., use tables to sit on. We will sort it out - everyone will fit! The project presentations will be arranged in separate sessions so that only <60 students are present at the same time.

All the best,

/Hedvig

Lärare kommenterade 2 december 2015

On Tuesday at 12-13, Jens will hold a help session in room 1448 on Lindstedtsv 3, floor 4. It is the room with entrance directly from the stairway, directly opposite the entrance to the computer halls.

This session will be useful for quite open questions where you need to discuss things. While waiting for this session, first try to pose your questions on the home page, so that all students can see the answers!

kommenterade 8 december 2015

Was the help session moved somewhere else?

kommenterade 8 december 2015

E3

kommenterade 8 december 2015

Sorry e31

kommenterade 10 december 2015

Hi Hedvig,​

    I am not sure, but I think you said that you were open to some suggestions for the content of the next class, scheduled on 15th December. I had a discussion with few course mates. We thought it might be a good idea if you could talk about the recently concluded NIPS Conference in Montreal. 

             I heard there was a overwhelming response from the academia as well the industry this year. We would love to hear about the recent developments in the field of machine learning especially the work related to the content taught to us in this course. What skills do you think might prove to be crucial for the academia as well as the industry in near future. 

Thank you

Lärare kommenterade 10 december 2015

That sounds like a really nice idea!

What do other students think about this?

Best,

/Hedvig

kommenterade 10 december 2015

I like the idea!

kommenterade 10 december 2015

Sounds like a great idea, really interested to hear about the frontier of the field :)

kommenterade 13 december 2015

It sounds great!

Lärare kommenterade 13 december 2015

Ok then, let us decide that the session on Tues is spent looking at the developments of the ML state of the art! I will guve a short overview of the discussions during the last few years and up to now. We can then have a short look at three papers and how they relate to this discussion. Best, Hedvig (on my way home from NIPS)

Lärare kommenterade 13 januari 2016

Now the detailed schedule for the project presentations is presented in the Schedule and Course Plan page. We are looking forward to seeing your presentations on Monday between 14 and 18, and receiving your reports via email on Monday at 12 noon!

Carl Henrik will not be able to make it unfortunately, but Jens and Hedvig are there to listen to you.

Please make sure that Hedvig has your slides on her computer before the start of your session - bring them on a stick to the lecture hall. Very strict 10 min time limits apply, since we are no less than 21 groups!

Feedback Nyheter