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Project

The project is performed in groups of 4-5 students in the period December 9, 2014 - January 19, 2015. To make the groups as homogeneous as possible in terms of ambition level for this course, we will divide you into groups dependent on grade performance on Assignments 1 and 2. PhD students will be placed in separate groups. The group division AND THE ASSIGNED PROJECTS TO EACH GROUP is found in this text document:

NOTE: We will by default only include students that have presented Assignment 1 and/or Assignment 2 in the groups. If you want to do the project, but are not in the list above, please send Hedvig Kjellström an email asap.

The task of the project is to reproduce the results presented in a published scientific article, describe the article orally and in written form to your peer students, and argue for and against the method presented in the article. From this you will learn how to read scientific articles, how to implement and use a particular method, how to argue for and against a method, and how to adapt the presentation of a method to different target groups (i.e., adapt the presentation of the method in the article - targeted to active researchers in Machine Learning - so that it is understandable to first year Master students in Machine Learning).

Below, you find lists of scientific articles; Each teacher has provided their own list, and will take responsibility for the supervision of the projects on their papers. IN THE TEXT DOCUMENT ABOVE, YOU FIND THE ARTICLE ASSIGNED TO YOUR GROUP.

Each group should send an email to Hedvig before or on December 9 with a ranked list of 5 articles that they would like to work on. In the list, you should identify each paper as (<Last name of first author>, <Publication year>).  Articles will then be distributed among groups in a manner so that all groups work on different articles, and each group gets an article with as high ranking as possible.

NOTE: This means that all students must be active December 5-9 in seeking out the other members of their group, agreeing on interesting papers.

Supervision

The group should plan and carry out the project autonomously. However, the teacher who listed the article you work with is available to answer questions, should you get stuck.

Carl Henrik is abroad but available over email December 6-23. All teachers are on holiday December 24-January 1.

Grading

The requirements for pass (i.e., E or higher) are

  • an implementation of the method and recreation of the experiments, according to the instructions below,
  • a written report according to the instructions below,
  • an oral presentation according to the instructions below.

Higher grades (A-D) are set based on

  • how well you are able to repeat the results in the article (or alternatively, how well you argue for deviations between the results in the article and your own results),
  • how well you are able to argue for and against the method in the article, and
  • how well you are able to present the method in the article, making it understandable to your peer students. Both the written and oral presentation are taken into account.

Implementation

Each group should implement the method as described in the paper. You may use any programming language. You should implement the entire algorithm "from scratch" to fully understand all details of it. there are exceptions to this, such as complex optimization schemes, which are too time consuming to implement - these exceptions are listed in connection to each paper.

You are not allowed to contact the authors and ask for their source code.

You will then perform the same experiments as those described in the article. Ideally, you should get the same results. If this is not the case, you must make an argument about possible reasons, and prove your argument by small experiments which you design and carry out yourself. A negative reproduction result together with a good argument gives an equally high grade as a positive reproduction result.

All group members must participate actively in the implementation, i.e., write code. Each piece of code that you write should have a comment stating who contributed to that piece of code. You do not have to submit the code for assessment, but be prepared to show it upon request. (For more information about code plagiarism, se General > Honor code in the menu to the left.)

Written Report

The article, the re-implementation, and your results are presented in a written report, to be sent to Hedvig Kjellström via email in pdf format before the oral presentation on January 19. The report should be at most 10 pages, with 12 pt font and about 2.5 cm margins, including references, images, and tables. In addition to the 10 pages, the report should have a cover page with title, group number, author list and (optional) abstract. The report should be written in (to a reasonable level) grammatically correct English.

In the report you should first describe the article on such a level of detail that your peer students in this course understand the method, and so that it is clear to the reader that you understand the method too.

You should then present your re-implementation of the method, and your reproduction of the results, again on such a level that your peer students understand what you have done, and so that it is clear to the reader what results you got and if, how, and why they deviate from the results presented in the original article.

Finally you should argue for and against the method, possibly suggesting improvements.

All statements made in the report (e.g., "method X is better than method Y") should be supported by either a reference to the original paper or report where the statement was made, or if the statement originates from you, you should explain why this statement is true.

A technically correct, well organized report with good language and a clear line of argument will receive a high grade. Missed hand-in deadline, violations of the length and formatting requirements, as well as statements not supported by references will have a heavy negative effect on the grade.

All group members must participate actively in the writing of the report. By adding a group member to the author list of the report, you certify that this person has written at least one section of the report.

Oral Presentation

You will also present your project to the other students of the course in a short oral presentation on January 19, 2015 at 9-12 in hall V3.

Each presentation is 10 minutes long and should follow the this format:

  • The aim of the article - what problem is addressed?
  • The method
  • The results that they get in the article
  • The results that you get
  • If there are differences - what are the reasons?
  • Arguments for and against the method

A clear, well organized presentation will receive a high grade. We can assure you that you will not get lower grades if you are nervous and make mistakes because of that. However, do not try to cram too much into the presentation - violations of the 10 minute time limit will have a negative effect on the grade.

Slides are optional, but if you have them they should be in pptx or pdf format. Bring the slides to the session on a memory stick, so that they can be uploaded to one computer in the beginning of the session.

All group members must participate actively in the oral presentation, i.e., talk for at least a minute.

Lärare Hedvig Kjellström skapade sidan 2 november 2014

Hedvig Kjellström flyttade sidan från Machine Learning, Advanced Course (DD2434) 2 november 2014

kommenterade 8 december 2014

Is it not possible to do the paper by Keith Grochow et al. “Style-based inverse kinematics” that we got teased with it in Carl's lecture in representation learning. It seems to be a good application of representation learning and has a very intuitive result.

Lärare kommenterade 8 december 2014

Hi,

Actually the Grochow paper is doing exactly what is in the paper by Lawrence that is suggested, only applied to human pose data. So if you want to do this, pick the paper by Lawrence and then apply it to Human motion capture data. I agree that the results are very intuitive and this application is really useful. 

Lärare kommenterade 12 december 2014

Hi,

It would be great if one person from each group that will be working on projects that I have suggested would contact me by email so that we can have a discussion of what I expect you to do. First have a read through of the paper, chat with your group mates and then contact me so that we have a somewhat similar basis of understanding.

Lärare kommenterade 12 december 2014

That sounds like a splendid idea, I would like to ask my groups to also send me a brief email with your view on what you should do in your project.

Formulating this email will also, besides giving me info, help you clarify to yourselves what your project is about.

Good luck!

/Hedvig

kommenterade 10 januari 2015

Hello,

We are writing the report and wanted to know if we should refer to the references of the paper when referenced by the paper when stating something. Or can one simply refer to the paper at hand?

kommenterade 10 januari 2015

Sorry for the meta like questions :P

Lärare kommenterade 12 januari 2015

Hi,

This is a tricky one, if we would cite all the way back to the originators of things Aristoteles would have a lot of citations. What I would say is that, cite as far back as what you have read, so if you have understood the point from the original paper just cite that but if you needed to go back another step and read cite this. I'm not sure if this makes it less confusing but its not something that is fundamental for this report, however it is an important point that will come up when you write your thesis but then you are required to do more of a background study which isn't really the case here.

Hope this helps.

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kommenterade 18 januari 2015

Hello,

Is the format for the oral presentation a totally ordered set? Or can we change the format somewhat? We would like to present the results of experiments together with the author.

Lärare Hedvig Kjellström ändrade rättigheterna 14 september 2015

Kan därmed läsas av alla och ändras av lärare.