Texture Networks: Feed-forward synthesis of textures and stylized images Ulyanov et al., arXiv, March 2016 During the summer break I mostly stayed away from news feeds and twitter, which induces terrible FOMO (Fear Of Missing Out) to start with. What great research was published / discussed that I missed? Was there a major industry announcement … Continue reading Texture networks: feed-forward synthesis of textures and stylized images
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Why should I trust you? Explaining the predictions of any classifier
“Why Should I Trust You? Explaining the Predictions of Any Classifier Ribeiro et al., KDD 2016 You’ve trained a classifier and it’s performing well on the validation set - but does the model exhibit sound judgement or is it making decisions based on spurious criteria? Can we trust the model in the real world? And … Continue reading Why should I trust you? Explaining the predictions of any classifier
The Morning Paper on Operability
I gave a 30 minute talk at the Operability.io conference yesterday on the topic of “The Morning Paper meets operability.” In a first for me, I initially prepared the talk as a long blog post, and then created a set of supporting slides at the end. Today’s post is the text of that talk - … Continue reading The Morning Paper on Operability
Mastering the game of Go with deep neural networks and tree search
Mastering the Game of Go with Deep Neural Networks and Tree Search Silver, Huang et al., Nature vol 529, 2016 Pretty much everyone has heard about AlphaGo’s tremendous Go playing success beating the European champion by 5 games to 0. In all the excitement at the time, less was written about how AlphaGo actually worked … Continue reading Mastering the game of Go with deep neural networks and tree search
Deep neural networks for YouTube recommendations
Deep Neural Networks for YouTube Recommendations Covington et al, RecSys '16 The lovely people at InfoQ have been very kind to The Morning Paper, producing beautiful looking "Quarterly Editions." Today's paper choice was first highlighted to me by InfoQ's very own Charles Humble. In it, Google describe how they overhauled the YouTube recommendation system using … Continue reading Deep neural networks for YouTube recommendations
Hints for computer system design
Hints for Computer System Design Butler Lampson, 1983 If there's been an unifying theme for The Morning Paper posts over the last couple of weeks, it's probably this: learning from the hard-won expertise of some of the greats in our field. So it seems fitting to end this run of papers with Butler Lampson's "Hints … Continue reading Hints for computer system design
The Rise of Worse is Better
Lisp: Good News, Bad News, How to Win Big Richard Gabriel, EuroPal 1990 While John Hughes was lamenting that the world at large didn't understand the benefits of functional programming, Richard Gabriel was considering the reasons for the difficulties within the Lisp community: "Lisp has done quite well over the last ten years... yet the … Continue reading The Rise of Worse is Better
Why Functional Programming Matters
Why Functional Programming Matters John Hughes, Research Topics in Functional Programming, 1990 (based on an earlier Computer Journal paper that appeared in 1989). 1989/1990 must have been a fairly dark time to be a functional programmer. Object-oriented programming was rising in prominence and the dream that industry would pay attention to functional programming looked like … Continue reading Why Functional Programming Matters
Data on the Outside versus Data on the Inside
Data on the Outside vs Data on the Inside Pat Helland, CIDR 2005 Another (modern) classic today, Pat Helland's wonderful 2005 paper on thinking about data in service oriented architectures. Sticking with the contemporary feel I'm going to write SOA as 'microservices' for the rest of this post. Helland shows us that we need to … Continue reading Data on the Outside versus Data on the Inside
On designing and deploying internet-scale services
On designing and deploying internet-scale services James Hamilton LISA '07 Want to know how to build cloud native applications? You'll be hard-pushed to find a better collection of wisdom, best practices, and hard-won experience than this 2007 paper from James Hamilton. It's amazing to think that all of this knowledge was captured and written down … Continue reading On designing and deploying internet-scale services
the morning paper 