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Reviewer Instructions for AISTATS 2014

Reviews must be entered electronically through the CMT system:

https://cmt.research.microsoft.com/AISTATS2014/

Review Content

Each review should begin with an overview of the paper summarising its main contributions. In particular some thought should be given to how the paper fits with the aims and topics of the conference (not interpreted overly narrowly) . The ideas presented should be related to previous work in the field.

The next section of the review should deal with major comments, issues that the reviewer sees as standing in the way of acceptance of the paper, or issues that should be addressed prior to publication.

The final section of the review should deal with any minor issues, such as typographical errors or spelling mistakes or areas where presentation could be improved.

Evaluation Criteria

Contributions of AISTATS papers can perhaps be categorised into four areas a) algorithmic, b) theoretical, c) unifying or d) application.

Algorithmic contributions may make a particular approach feasible for the first time or may extend the applicability of an approach (for example allowing it to to be applied to very large data sets).

A theoretical contribution should provide a new result about a model or algorithm. For example convergence proofs, consistency proofs or performance guarantees.

A unifying contribution may bring together several apparently different ideas and show how they are related, providing new insights and directions for future research.

Finally, an application contribution should typically have aspects that present particular statistical challenges which required solution in a novel way or through clever adaptation of existing techniques.

A paper may exhibit one or more of these contributions, each of them are important in advancing the state of the art in the field. Of course, at AISTATS we are also particularly keen to see work which relates machine learning and statistics or highlights novel connections between the fields.

When reviewing bear in mind that one of the most important aspects of a successful conference paper is that it should be thought provoking. Thought provoking papers sometimes generate strong reactions on initial reading, which may sometimes be negative. However, if the paper genuinely represents a paradigm shift it may take a little longer than a regular paper to come around to the author's way of thinking. Keep an eye out for such papers, although they may take longer to review, if they do represent an important advance the effort will be well worth it.

Confidentiality and Double Blind Process

AISTATS 2014 is a double blind reviewed conference. Whilst we expect authors to remove information that will obviously reveal their identity, we also expect that reviewers don't take positive steps to try and uncover the authors' identity.

We are very happy for authors to submit material that they have placed on line as tech reports (such as in arXiv), or that they have submitted to existing workshops which do not produce published proceedings. This can clearly present a problem with regard to anonymisation. Please do not seek out such reports on line in an effort to deanonymise.

The review process is double blind. Authors do not know reviewer identities, and this includes any authors on the senior programme committee (the area chairs). However, area chairs do see reviewer identities. Also, during the discussion phase reviewer identities will be made available to other reviewers. In other words whilst the authors will not know your identity your co-reviewers will. This should help facilitate discussion of the papers.

The AISTATS reviewing process is confidential. By agreeing to review you agree not to use ideas and results from submitted papers in your work. This includes research and grant proposals. This applies unless that work has appeared in other publicly available formats, for example technical reports or other published work. You also agree not to distribute submitted papers or the ideas to anyone else unless permission is gained from the program chairs.

The CMT Reviewing System

The first step in the review process is to enter conflicts of interests. These conflicts can be entered as domain names and also by marking specific authors with whom you have a conflict. The use of double blind reviewing means you may not able to determine the papers you have a conflict with, so it is important you go through this list carefully and mark any conflicts. You should mark a conflict with anyone who is or ever was your student or mentor, is a current or recent colleague, or is a close collaborator. If in doubt, it's probably better to mark a conflict, in order to avoid the appearance of impropriety. Your own username should be automatically marked as a conflict, but sometimes the same person may have more than one account, in which case you should definitely mark your other accounts as a conflict as well. If you do not mark a conflict with an author, it is assumed that you do not have a conflict by default.

CMT also requests subject information which will be used to assist allocation of reviewers to papers. Please enter relevant keywords to assist in paper allocation.

You can revise your review multiple times before the submission. Your formal invite to be a reviewer came from the CMT system. The email address used in this invite is your login, you can change your password with a password reset from the login screen.

Supplementary Material

Supplementary material is allowed by AISTATS 2014. For example, this supplementary material could include proofs, video, source code or audio. As a reviewer you should feel free to make use of this supplementary material to help in your review.

Simultaneous Submission

Simultaneous submission to other conference venues in the areas of machine learning and statistics is not permitted.

Simultaneous submission to journal publications of significantly extended versions of the paper is permitted, as long as the publication date of the journal is not before 2014.

Some parts of these reviewer instructions are based on those for NIPS.