CompSci Weekend SuperThread (June 21, 2019) Computer Science |
- CompSci Weekend SuperThread (June 21, 2019)
- Differential Evolution question (fitness and objective functions)
- Transformation of XML Documents with Prolog: "LTL is extensible as much as possible to break through the limited syntax of XSL-T. The task restricts to XML documents, but essentially all hierarchical markup documents are affected." [abstract + link to 5p PDF]
- From Foodie Pic to Your Plate: Generating Recipes With Facebook AI
- Principled Machine Learning: Practices and Tools for Efficient Collaboration - Transparency, Auditability, Reproducibility and Scalability in ML Projects
- Creating educational gifs
- Leading Researchers Publish ‘Climate Change + AI’ Document
CompSci Weekend SuperThread (June 21, 2019) Posted: 20 Jun 2019 06:06 PM PDT /r/compsci strives to be the best online community for computer scientists. We moderate posts to keep things on topic. This Weekend SuperThread provides a discussion area for posts that might be off-topic normally. Anything Goes: post your questions, ideas, requests for help, musings, or whatever comes to mind as comments in this thread. Pointers
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Differential Evolution question (fitness and objective functions) Posted: 20 Jun 2019 05:40 PM PDT I have very blurred lines of comprehension on what distinguishes fitness function and objective function. I think the problem is that in a lot of examples they seem to overlap and return the same value or its inverse. I can't find examples where they differ enough for me to get a clear grasp on what the role of each function is? [link] [comments] |
Posted: 21 Jun 2019 12:54 AM PDT |
From Foodie Pic to Your Plate: Generating Recipes With Facebook AI Posted: 20 Jun 2019 11:27 AM PDT |
Posted: 20 Jun 2019 12:08 PM PDT |
Posted: 20 Jun 2019 06:34 AM PDT Hey there. I'm just learning about CNNs and related material for my thesis research and I'm coming across pages that have these very educational gifs that explain topics. One example is on this page http://cs231n.github.io/convolutional-networks/ . About half way down the page there's a movable example that's performing examples of convolutions. Does anyone know how to make these? There are also other examples on this page of what I mean that are slightly different I think: https://towardsdatascience.com/a-comprehensive-guide-to-convolutional-neural-networks-the-eli5-way-3bd2b1164a53 [link] [comments] |
Leading Researchers Publish ‘Climate Change + AI’ Document Posted: 20 Jun 2019 08:31 AM PDT |
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