machine learning – Page 56 – Andrew Fairless, Ph.D.

What I Read: Guide to Graph Neural Networks

By Andrew Fairless on December 20, 2020December 8, 2020

https://medium.com/dair-ai/an-illustrated-guide-to-graph-neural-networks-d5564a551783 An Illustrated Guide to Graph Neural NetworksA breakdown of the inner workings of GNNs…Rishabh AnandMar 30 “Here, I’ll cover the basics of a simple Graph Neural Network (GNN) andContinue readingWhat I Read: Guide to Graph Neural Networks

What I Read: sub-linear deep learning algorithm

By Andrew Fairless on December 19, 2020December 4, 2020

https://www.kdnuggets.com/2020/03/deep-learning-breakthrough-sub-linear-algorithm-no-gpu.html Deep Learning Breakthrough: a sub-linear deep learning algorithm that does not need a GPU?By Anshumali Shrivastava, Rice University. “Backpropagation is not an efficient algorithm…. The core idea behind theContinue readingWhat I Read: sub-linear deep learning algorithm

What I Read: Transformers Graph Neural Networks

By Andrew Fairless on December 17, 2020December 4, 2020

https://graphdeeplearning.github.io/post/transformers-are-gnns/ Transformers are Graph Neural NetworksChaitanya JoshiFeb 12, 2020 “Through this post, I want to establish links between Graph Neural Networks (GNNs) and Transformers. I’ll talk about the intuitions behindContinue readingWhat I Read: Transformers Graph Neural Networks

What I Read: Neural State Machine

By Andrew Fairless on December 16, 2020December 4, 2020

https://arxiv.org/abs/1907.03950 Learning by Abstraction: The Neural State MachineDrew A. Hudson, Christopher D. Manning “We introduce the Neural State Machine, seeking to bridge the gap between the neural and symbolic viewsContinue readingWhat I Read: Neural State Machine

What I Read: Kids’ brains building AI

By Andrew Fairless on December 15, 2020December 3, 2020

https://www.vox.com/future-perfect/2019/2/28/18239993/artificial-intelligence-children-machine-learning-alison-gopnik-psychology Kids’ brains may hold the secret to building better AIby Sigal Samuel “It’s called Moravec’s paradox: The things we thought would be hard — like playing chess — areContinue readingWhat I Read: Kids’ brains building AI

What I Read: The New Business of AI

By Andrew Fairless on December 14, 2020December 3, 2020

The New Business of AI (and How It’s Different From Traditional Software) The New Business of AI (and How It’s Different From Traditional Software)by Martin Casado and Matt Bornstein “JustContinue readingWhat I Read: The New Business of AI

What I Read: Neighbourhood Components Analysis

By Andrew Fairless on December 13, 2020December 1, 2020

https://kevinzakka.github.io/2020/02/10/nca/ Kevin’s BlogkNN classification using Neighbourhood Components AnalysisFeb 10, 2020 “Long story short, NCA allows you to learn a linear transformation of your data that maximizes k-nearest neighbours performance. ByContinue readingWhat I Read: Neighbourhood Components Analysis

What I Read: Reproducible Machine Learning

By Andrew Fairless on December 12, 2020December 1, 2020

https://thegradient.pub/independently-reproducible-machine-learning/ Independently Reproducible Machine Learning06.Feb.2020Edward Raff “How reproducible is the latest ML research, and can we begin to quantify what impacts its reproducibility? This question served as motivation for myContinue readingWhat I Read: Reproducible Machine Learning

What I Read: Economics of AI

By Andrew Fairless on December 11, 2020December 1, 2020

https://thegradient.pub/the-economics-of-ai-today/ The Economics of AI Today18.Jan.2020Juan Mateos-Garcia “…a group of distinguished economists gathered in Toronto to set out a research agenda for the Economics of Artificial Intelligence (AI). They coveredContinue readingWhat I Read: Economics of AI

Tag: machine learning