Speed Reviewing

Add to your list(s) Download to your calendar using vCal

• All Participants
• Thursday 29 October 2009, 14:00-15:30
• Engineering Department, CBL Room 438.

If you have a question about this talk, please contact Shakir Mohamed.

For next week’s ML RCC we are going to try the following experiment. Come prepared!

—- Peer Speed-Review Exercise RCC :

- Bring a red pen and two printed copies of a draft of a paper you are currently working on. It could either be a submission in preparation (e.g. to AISTATS ), or something under revision. It can even be a very rough draft, or outline of a paper.

- We will pair up RCC participants into teams of 2.

- During the RCC , we will randomly assign each team two papers to speed-review. Both reviewers in a team will independently review both papers, spending 30 minutes on each paper only, paying particular attention to the abstract, introduction, motivation, structure and conclusion. Obviously 30 minutes is not enough time to give feedback on details of the paper. The reviewers will independently mark up each paper with comments.

- During the next 20 minutes of the RCC , each team will discuss the two papers they reviewed and reach a consensus about strengths or weaknesses of the papers, and additional feedback to give the author.

- Final 10 minutes we will wrap up with a discussion of any interesting findings from this exercise.

- After the RCC the marked-up papers go back to the authors, and optionally the reviewers and authors can further discuss the paper to get more constructive feedback.

This talk is part of the Machine Learning Reading Group @ CUED series.

This talk is included in these lists:

• All Talks (aka the CURE list)
• Cambridge Centre for Data-Driven Discovery (C2D3)
• Cambridge Forum of Science and Humanities
• Cambridge Language Sciences
• Cambridge University Engineering Department Talks
• Cambridge talks
• Centre for Smart Infrastructure & Construction
• Chris Davis' list
• Engineering Department, CBL Room 438
• Featured lists
• Guy Emerson's list
• Hanchen DaDaDash
• Inference Group Journal Clubs
• Inference Group Summary
• Information Engineering Division seminar list
• Interested Talks
• ML
• Machine Learning Reading Group
• Machine Learning Reading Group @ CUED
• Machine Learning Summary
• Quantum Matter Journal Club
• Required lists for MLG
• School of Technology
• Simon Baker's List
• TQS Journal Clubs
• Trust & Technology Initiative - interesting events
• bld31
• custom
• ndk22's list
• rp587
• yk373's list

Note that ex-directory lists are not shown.