About Adrian Colyer

Adrian Colyer was CTO of SpringSource, then CTO for Apps at VMware and subsequently Pivotal. He is now a Venture Partner at Accel Partners in London, working with early stage and startup companies across Europe. If you’re working on an interesting technology-related business he would love to hear from you: you can reach him at acolyer at accel dot com.

Adrian Colyer Posts (15)

  • Beyond news contents: the role of social context for fake news detection - 07 Mar 2019
    Today we’re looking at a more general fake news problem: detecting fake news that is being spread on a social network. This is a summary of a recent paper which demonstrates why we should also look at the social context: the publishers and the users spreading the information!
  • TensorFlow.js: Machine learning for the web and beyond - 28 Feb 2019
    TensorFlow.js brings TensorFlow and Keras to the the JavaScript ecosystem, supporting both Node.js and browser-based applications. Read a summary of the paper which describes the design, API, and implementation of TensorFlow.js.
  • A comprehensive survey on graph neural networks - 15 Feb 2019
    This article summarizes a paper which presents us with a broad sweep of the graph neural network landscape. It’s a survey paper, so you’ll find details on the key approaches and representative papers, as well as information on commonly used datasets and benchmark performance on them.
  • Deep learning scaling is predictable, empirically - 10 May 2018
    This study starts with a simple question: “how can we improve the state of the art in deep learning?”
  • PrivacyGuide: Towards an implementation of the EU GDPR on Internet privacy policy evaluation - 03 May 2018
    Studies have shown that only 1% or less of total users click on privacy policies, and those that do rarely actually read them. The GDPR requires clear succinct explanations and explicit consent, but that’s not the situation on the ground right now, and it’s hard to see that changing overnight on May 25th.
  • DeepSense: A unified deep learning framework for time-series mobile sensing data processing - 02 Aug 2017
    Compared to the state-of-art, DeepSense provides an estimator with far smaller tracking error on the car tracking problem, and outperforms state-of-the-art algorithms on the HHAR and biometric user identification tasks by a large margin.
  • Usage Patterns and the Economics of the Public Cloud - 06 Jul 2017
    Research in economics and operations management posits that dynamic pricing is critically important when capacity is fixed (at least in the short run) and fixed costs represent a substantial fraction of total costs.
  • Silver Blog, June 2017Understanding Deep Learning Requires Re-thinking Generalization - 16 Jun 2017
    What is it that distinguishes neural networks that generalize well from those that don’t? A satisfying answer to this question would not only help to make neural networks more interpretable, but it might also lead to more principled and reliable model architecture design.
  • Learning to Learn by Gradient Descent by Gradient Descent - 02 Feb 2017
    What if instead of hand designing an optimising algorithm (function) we learn it instead? That way, by training on the class of problems we’re interested in solving, we can learn an optimum optimiser for the class!
  • Artificial Intelligence and Life in 2030 - 15 Dec 2016
    Read this engaging overview of a report from the Stanford University 100 year study of Artificial Intelligence, “a long-term investigation of the field of Artificial Intelligence (AI) and its influences on people, their communities, and society.”

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