To set some sort of a cut-off point, your comment has to be posted within 24 hours from this contest going live (see date/time atop the teaser). Unlike contests at a lot of other websites, this one is not limited to the US – wherever you live, you’re eligible. You can troll, you can butter up, you can beat OSNews and its team senseless with words. Make it as absurd and surreal as possible. For your short story to be eligible, it needs to be about at least the following things:Ī few sentences is enough this isn’t about length, it’s about absurdism. Because this is OSNews, and because I just thought of this contest like 56 seconds ago, it does have a few crazy twists. So, what do you have to do to get your hands on a free copy? Simple, really: write a very short story, and post it in the comments. The copies are provided by BinaryAge, the company behind TotalFinder and several other Mac OS X tools. To extend the holiday spirit a for just a little longer, we’re giving away three copies of TotalFinder for the Mac. It’s the start of the new year, we’re all recovering from our various new years’ eve obligations, and we’re sad we all have to go to work again tomorrow (well, except for me – I work from home). We’ve got three free copies of TotalFinder to hand out, so read on to find out how you can win one! Learn a new language / help translate documents very clever crowdsourcing.A few weeks ago, we took a look at TotalFinder, a collection of add-ons to the Mac OS X Finder that fixes some of its shortcomings, adds some welcome features, and in all, makes it a little more pleasant to use. "a unique translation tool combining an editorial dictionary and a search engine" Writing: pandoc, LyX, ShareLatex, LyX, ObsidianĮvents with one click), TotalFinder, SSHFS language tools linguee Languages: Julia, R, Matlab, Python, bash Work tools Ergonomics: standing desk, high chair, white boards If your problem is computationally intensive, consider learningĭistributed programming (GPU or cluster). Emacs users can use IRC by doing "M-x erc". Q&A sites for Math: mathoverflow, math.stackexchangeįor R, visit the #R channel on FreeNode ( IRC). Borri, editors, Working Notes for the CLEF 2004 Workshop, pages 91-98, 2004. de Rijke - The University of Amsterdam at CLEF 2004, In: C. Paliouras (Eds.), Proceedings of the international conference on User Modeling (LNAI 4511) (pp. Koedinger - Evaluating a Simulated Student using Real Students Data for Training and Testing, In C. Greer (Eds.), Proceedings of the international conference on Artificial Intelligence in Education (pp. Koedinger (2007) - Predicting students performance with SimStudent that learns cognitive skills from observation. In Proceedings of the International Conference on Intelligent Tutoring Systems. Koedinger (2008) - Why tutored problem solving may be better than example study: Theoretical implications from a simulated-student study. Mathematically trivial, but apparently original. Lacerda - Upper-Bounding Proof Length with the Busy Beaver (2008) - I derive an (uncomputable) upper bound on the length of the shortest proof of any given statement, as a function of the length of the statement and briefly discuss implications. This is useful when it may be the case that more than one, but not all error terms are Gaussian. How to intelligently combine LiNGAM with methods based on conditional independence tests. Shimizu - Causal discovery of linear acyclic models with arbitrary distributions Proceedings of the 24th Conference on Uncertainty in Artificial Intelligence (UAI-2008) by Richardson's CCD), and allows us to relax the faithfulness assumption. Hoyer - Discovering Cyclic Causal Models by ICA (UAI2008), video lecture with slides) extends LiNGAM to discover cyclic models The non-Gaussian model leads to a finer level of identifiability than what can be achieved in the Gaussian case (e.g. Lacerda - Identification of gene modules using a generative model for relational data - UBC Master's thesis (2010), supervised by Jennifer Bryan. Capano - Smart Proofs via Smart Contracts: Succinct and Informative Mathematical Derivations via Decentralized Markets Introduction to Machine Learning and Bayesian inference ( slides), 45 minutes. Introduction to Kolmogorov Complexity (with Liliana Salvador) ( slides), 45 minutes.
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