Why neurons have thousands of synapses, a theory of sequence memory in neocortex Hawkins & Ahmad, Front. Neural Circuits 2016 It all began with a fascinating lunchtime conversation with Martin Thompson (@mjpt777), who mentioned to me a thought-provoking video he’d seen online from Jeff Hawkins regarding models of behaviour in the brain. A few days … Continue reading Why neurons have thousands of synapses, a theory of sequence memory in neocortex
Tag: Machine Learning
ActiveClean: Interactive data cleaning for statistical modeling
ActiveClean: Interactive data cleaning for statistical modeling Krishnan et al., VLDB 2016 Yesterday we saw that one of the key features of a machine learning platform is support for data analysis, transformation and validation of datasets used as inputs to the model. In the TFX paper, the authors reference ActiveClean as an example of data … Continue reading ActiveClean: Interactive data cleaning for statistical modeling
TFX: A TensorFlow-based production scale machine learning platform
TFX: A TensorFlow-based production scale machine learning platform Baylor et al., KDD'17 What world-class looks like in online product and service development has been undergoing quite the revolution over the last few years. The series of papers we've been looking at recently can help you to understand where the bar is (it will have moved … Continue reading TFX: A TensorFlow-based production scale machine learning platform
Google Vizier: A service for black-box optimization
Google Vizier: a service for black-box optimization Golovin et al., KDD'17 We finished up last week by looking at the role of an internal (or external) experimentation platform. In today's paper Google remind us that such experimentation is just one form of optimisation. Google Vizier is an internal Google service for optimising pretty much anything. … Continue reading Google Vizier: A service for black-box optimization
Struc2vec: learning node representations from structural identity
struc2vec: learning node representations from structural identity Ribeiro et al., KDD'17 This is a paper about identifying nodes in graphs that play a similar role based solely on the structure of the graph, for example computing the structural identity of individuals in social networks. That's nice and all that, but what I personally find most … Continue reading Struc2vec: learning node representations from structural identity
Automatic database management system tuning through large-scale machine learning
Automatic database management system tuning through large-scale machine learning Aken et al. , SIGMOD'17 Achieving good performance in DBMSs is non-trivial as they are complex systems with many tunable options that control nearly all aspects of their runtime operation. OtterTune uses machine learning informed by data gathered from previous tuning sessions to tune new DBMS … Continue reading Automatic database management system tuning through large-scale machine learning
Neural architecture search with reinforcement learning
Neural architecture search with reinforcement learning Zoph & Le, ICLR'17 Earlier this year we looked at 'Large scale evolution of image classifiers' which used an evolutionary algorithm to guide a search for the best network architectures. In today's paper, Zoph & Le also demonstrate that learning network architectures (and also in their case recurrent cell … Continue reading Neural architecture search with reinforcement learning
End-to-end optimized image compression
End-to-end optimized image compression Ballé et al., ICLR'17 We'll be looking at some of the papers from ICLR'17 this week, starting with "End-to-end optimized image compression" which makes a nice comparison with the Dropbox JPEG compression paper that we started with last week. Of course you won't be surprised to find out that the authors … Continue reading End-to-end optimized image compression
Beyond the words: predicting user personality from heterogeneous information
Beyond the words: predicting user personality from heterogeneous information Wei et al., WSDM 2017 Here's a very topical paper! You may have seen the recent Motherboard piece, "The data that turned the world upside down," describing how personality profiling was used to provide tailored messages to voters in the recent American elections. In the interest … Continue reading Beyond the words: predicting user personality from heterogeneous information
European Union regulations on algorithmic decision making and a “right to explanation”
European Union regulations on algorithmic decision-making and a “right to explanation” Goodman & Flaxman, 2016 In just over a year, the General Data Protection Regulation (GDPR) becomes law in European member states. This paper focuses on just one particular aspect of the new law, article 22, as it relates to profiling, non-discrimination, and the right … Continue reading European Union regulations on algorithmic decision making and a “right to explanation”
the morning paper 