- A solution to an exposition problem « Gowers’s Weblog
- “Let me explain the title of this post by quoting from Timothy Chow’s highly recommended expository article A beginner’s guide to forcing: “All mathematicians are familiar with the concept of an open research problem. I propose the less familiar concept of an open exposition problem. Solving an open exposition problem means explaining a mathematical subject in a way that renders it totally perspicuous. Every step should be motivated and clear; ideally, students should feel that they could have arrived at the results themselves.—
- Seb’s Open Research: Stocks, Flows, and Upkeep in Social Media
- Seb Paquet’s exegesis of an experiment in mass collaborative drawing. Vandalism, designing good social media, persistent social structures, and many other topics…
- ICML Discussion Site [ICML Discussion]
- “The aim of this site is to enable the research community to discuss papers accepted to ICML [International Conference on Machine Learning]. Each paper accepted to ICML 2008 has a page on this site. Each page has details of the paper and a discussion thread. “
- Meatball Wiki: WikiLifeCycle
- CiteULike: Group on Statistical Machine Learning
- Life on the lattice: Openness >> fraud
- “Schön’s deception was only possible because the researchers who tried and failed to replicate his results didn’t have access to his primary data. Once doubts had been raised over the appearance of two completely identical graphs supposedly representing two completely different sets of experimental data, Schön’s primary data were subjected to close scrutiny and were found to be non-existent — his labbooks had been destroyed, and his samples were damaged beyond recovery. This raises the question whether it would have been possible to even contemplate such a fraud in an environment where scientists are genuinely expected to hide nothing, and in particular to make their primary data publicly available after publication.”
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