Can Stack Exchange save scientific peer review? [Update]
One of the few things everybody seems to agree on is that the scientific review process, especially for computer science, is broken. I wont go into details here as there are many sources on the net.
But personally I found Yann LeCun’s pamphlets for “A New Publishing Model in Computer Science” inspiring. He proposes an open, karma-based online repository which I will summarize as follows:
- In this system authors post their papers as soon as they feel, that there finished. The publication is put under version control and is immediately citable.
- “Reviewing Entities” (RE), individuals or groups like editorial boards, then choose papers they want to review or accept review requests from authors.
- REs do not “own” papers exclusively, so RE can choose to review any paper at any time. Papers can be reviewed by multiple REs.
- The reviews are published with the paper and are themselves citable documents like regular publications.
- Reviews are furthermore rated by readers. Good reviews will generate “karma” points for the RE, to show the usefulness of their review.
- Additionally RE’s “karma” will increase if they are the first to positively review a paper which is than later rated as high quality by other REs as well. As a result RE will have an incentive to be the first to review good papers.
I will not repeat LeCun’s explanations on how it works in detail and why it would be superior to the existing system. Instead I want to point out how very similar this approach is to the Stack Exchange (SE) QA websites. Stack Exchange is a network of over 70 Q&A websites, with stackoverflow.com, a Q&A site on programming, being the first and largest one. On Stack Exchange websites everyone can ask questions which can be answered by all the members of the community. Both questions and answers will be rated by the community, so users are incentivized to write useful answers to questions which are relevant to many other users in order to gain reputation.
Especially if you have used a SE website, it is hard to ignore the similarities. Even though the SE framework was build to solve a different problem, I can see it being adapted to act as a repository for LeCun’s publishing model. Publications would be questions and reviews would be answers. I can only make out following necessary changes.
- There needs to support for groups (RE),
- high level users should not be permitted to change other people’s posts anymore and
- the ‘answer’ functionality has to be removed.
Everyone who follows the two founders of Stack Exchange, Jeff Atwood and Joel Spolsky, knows, how determine both are to remove all diversion of their vision for Stack Exchange, so it wouldn’t be possible to be officially part of the SE community. But there is also OSQA, the open source copy of SE. Using this service makes it seem possible to implement the necessary features.
So, what do you think? Can Stack Exchange save scientific peer review?
[UPDATE]
LeCun was so generous to comment on my article via e-mail. He confirmed that his views on the peer review process and his model haven’t changed and agrees that creating the technical infrastructure shouldn’t be too hard. He already received several offers from possible volunteers, but the project is still missing a highly competent developer(-team) to “own” the project.
Disclaimer: I am not the first one to bring Stack Exchange on the table, but I found the other approach far less concrete.
Paper: Rendering Synthetic Objects into Legacy Photographs
Inserting 3D objects into existing photographs
This fascinating video presents a new method to insert 3D objects into existing photographs. It is based on the research of Kevin Karsch, Varsha Hedau, David Forsyth and Derek Hoiem (all University of Illinois at Urbana-Champaign). Their main contribution is the algorithm, which generates the light model for the scene. The algorithm needs only one photograph and a few manual markings by a novice user together with a ground truth data set to create a near real life insertion. The ground truth data set was generated with 200 images from 20 indoor scenes under varying lighting conditions.
The video is well done and I am surprised whats possible, but I like to see how much user input is really necessary and how well the algorithm and the ground truth perform with other images. What do you think?
More details can be found at Kevin Karsch’s website.
Who is collaborating?
In my scarce spare time, I have written Collabgraph to visualize connections between authors of scientific publications.
This python script reads a (your) bibtex file and draws a graph in which all the nodes are authors and the edges represent that the two authors have collaborated (or at least wrote a paper together).
On the right is the graph created by from the references used in my diploma thesis. You can immediately see what central role Eakins, Meier and Flickner played.
Collabgraph requires only the pygraphviz library, which can installed with “easy_install pygraphviz”.
You can find the sourcode and the example at bitbucket.org.
I am looking forward to your feedback!!!
How to create good and fast Matlab code
As most of the readers of this blog land on one of the pages with the Matlab applications, I thought I collect some of my resources I use to write Matlab code.
First start with the official Mathworks help on how to write good code
- Programming Tips
- And maximizing performance
- MATLAB Programming Style Guidelines
- Good MATLAB Programming Practices
than we have this 33-page tutorial “Writing Fast MATLAB Code” (PDF)
followed by the Recorded Webinar: Handling Large Data Sets Efficiently in MATLAB
For asking questions, I enjoy the Stackoverflow community. Here are two examples of answers you get for generall Matlab questions.
So, I hope you find these links more helpful than overwhelming.
Please leave a comment if you have anything to add!
On the importance of context
For people who just start thinking about computer vision, it is of hard to understand why computers have such a difficult time finding faces in images, even though it is so easy for us.
Adding to one of my earlier articles about why is vision hard, which points out, that computers are missing concepts, there is another reason. They are also missing context. It is so easy for us, to spot faces, because we know were to look for them, where to expect them. When we see a person, we know were to look for the face, and when we see a house, we know, that we wont find a face. But computers don’t. And to show you that even we are lost without context I present you this nice picture with the coffee beans. Your job is to find the face.

Did you find the face? Probably you didn’t find it at once, but started to scan the picture till you found it. It took me nearly 30s,which is so much slower, than any recent software.
So how can we improve our algorithm with context?
p.s.
About the picture. I got it from a very interesting talk held at TID by Aleix M Martinez from the Ohio State University on classification. His main point, PCA and LDA. For starters check out his paper PCA versus LDA (2001).

