The curious case of the PDF converter that likes Mozart: dissecting and mitigating the privacy risk of personal cloud apps Harkous et al., PoPET '16 This is the paper that preceded "If you can't beat them, join them" we looked at yesterday, and well worth interrupting our coverage of CODASPY '17 for. Harkous et al., … Continue reading The curious case of the PDF converter that likes Mozart
Author: adriancolyer
Venture Partner with Accel in London, author of 'The Morning Paper'
If you can’t beat them, join them: a usability approach to interdependent privacy in cloud apps
If you can't beat them, join them: a usability approach to interdependent privacy in cloud apps Harkous & Aberer, CODASPY '17 I'm quite used to thinking carefully about permissions before installing a Chrome browser extensions (they all seem to want permission to see absolutely everything - no thank you!). A similar issue comes up with … Continue reading If you can’t beat them, join them: a usability approach to interdependent privacy in cloud apps
A study of security vulnerabilities on Docker Hub
A study of security vulnerabilities on Docker Hub Shu et al., CODASPY '17 This is the first of five papers we'll be looking at this week from the ACM Conference on Data and Application Security and Privacy which took place earlier this month. Today's choice is a study looking at image vulnerabilities for container images … Continue reading A study of security vulnerabilities on Docker Hub
BBR: Congestion-based congestion control
BBR: Congestion-based congestion control Cardwell et al., ACM Queue Sep-Oct 2016 With thanks to Hossein Ghodse (@hossg) for recommending today's paper selection. This is the story of how members of Google's make-tcp-fast project developed and deployed a new congestion control algorithm for TCP called BBR (for Bandwidth Bottleneck and Round-trip propagation time), leading to 2-25x … Continue reading BBR: Congestion-based congestion control
Stochastic program optimization
Stochastic program optimization Schkufza et al., CACM 2016 Yesterday we saw that DeepCoder can find solutions to simple programming problems using a guided search. DeepCoder needs a custom DSL, and a maximum program length of 5 functions. In 'Stochastic program optimization' Schkufza et al. also use a search strategy to generate code that meets a … Continue reading Stochastic program optimization
DeepCoder: Learning to write programs
DeepCoder: Learning to write programs Balog et al., ICLR 2017 I'm mostly trying to wait until the ICLR conference itself before diving into the papers to be presented there, but this particular paper follows nicely on from yesterday, so I've decided to bring it forward. In 'Large scale evolution of image classifiers' we saw how … Continue reading DeepCoder: Learning to write programs
Large-scale evolution of image classifiers
Large-scale evolution of image classifiers Real et al., 2017 I'm sure you noticed the bewildering array of network architectures in use when we looked at some of the top convolution neural network papers of the last few years last week (Part 1, Part2, Part 3). With sufficient training data, these networks can achieve amazing feats, … Continue reading Large-scale evolution of image classifiers
Ethically aligned design
The IEEE Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems. Ethically Aligned Design: A Vision For Prioritizing Wellbeing With Artificial Intelligence And Autonomous Systems, Version 1. IEEE, 2016. http://standards.ieee.org/develop/indconn/ec/autonomous_systems.html. Something a little different for today... the IEEE recently put out a first version of their "Ethically Aligned Design" report for public … Continue reading Ethically aligned design
A miscellany of fun deep learning papers
To round out the week, I thought I'd take a selection of fun papers from the 'More papers from 2016' section of top 100 awesome deep learning papers list. Colorful image colorization, Zhang et al., 2016 Texture networks: feed-forward synthesis of textures and stylized images Generative visual manipulation on the natural image manifold, Zhu et … Continue reading A miscellany of fun deep learning papers
Recurrent Neural Network models
Today we're pressing on with the top 100 awesome deep learning papers list, and the section on recurrent neural networks (RNNs). This contains only four papers (joy!), and even better we've covered two of them previously (Neural Turing Machines and Memory Networks, the links below are to the write-ups). That leaves up with only two … Continue reading Recurrent Neural Network models
the morning paper 