HyperLogLog in Practice: Algorithmic Engineering of a State of the Art Cardinality Estimation Algorithm - Heule et al. 2013 Continuing on the theme of approximations from yesterday, today's paper looks at what must be one of the best known approximate data structures after the Bloom Filter, HyperLogLog. It's HyperLogLog with a twist though - a … Continue reading HyperLogLog in Practice: Algorithmic Engineering of a State of the Art Cardinality Estimation Algorithm
Month: March 2016
MacroBase: Analytic Monitoring for the Internet of Things
MacroBase: Analytic Monitoring for the Internet of Things - Bailis et al. 2016 It looks like Peter Alvaro is not the only one to be doing some industrial collaboration recently! MacroBase is the result of Peter Bailis' collaboration with Cambridge Mobile Telematics (CMT), an IoT company. The topic at hand is analytic monitoring - detecting … Continue reading MacroBase: Analytic Monitoring for the Internet of Things
A Taxonomy of Attacks and a Survey of Defence Mechanisms for Semantic Social Engineering Attacks
A Taxonomy of Attacks and a Survey of Defence Mechanisms for Semantic Social Engineering Attacks - Heartfield and Loukas 2015 This paper is concerned with semantic social engineering: the manipulation of the user-computer interface to deceive a user and ultimately breach a computer system's information security. Semantic attack exploits include phishing, file masquerading (disguising file … Continue reading A Taxonomy of Attacks and a Survey of Defence Mechanisms for Semantic Social Engineering Attacks
Secrets, Lies, and Account Recovery: Lessons from the Use of Personal Knowledge Questions at Google
Secrets, Lies, and Account Recovery: Lessons from the Use of Personal Knowledge Questions at Google - Bonneau et al. 2015 What was your mother's maiden name? What was your city of birth? What was the name of your first school? I don't know about you, but I always groan inwardly when a website asks such … Continue reading Secrets, Lies, and Account Recovery: Lessons from the Use of Personal Knowledge Questions at Google
Strategic Dialogue Management via Deep Reinforcement Learning
Strategic Dialogue Management via Deep Reinforcement Learning - Cuayahuitl et al. 2015 If computers learning to play Atari arcade games by themselves isn't really your thing, perhaps you're more into board games? How about a Deep Reinforcement Learning system that learns how to trade effectively in Settlers of Catan! Again, we're not talking about a … Continue reading Strategic Dialogue Management via Deep Reinforcement Learning
Memory Networks
Memory Networks Weston et al. 2015 As with the Neural Turing Machine that we look at yesterday, this paper looks at extending machine learning models with a memory component. The Neural Turing Machine work was developed at Google by the DeepMind team, today's paper on Memory Networks was developed by the Facebook AI Research group. … Continue reading Memory Networks
Neural Turing Machines
Neural Turing Machines - Graves et al. 2014 (Google DeepMind) A Neural Turing Machine is a Neural Network extended with a working memory, which as we'll see, gives it very impressive learning abilities. A Neural Turing Machine (NTM) architecture contains two basic components: a neural network controller and a memory bank. Like most neural networks, … Continue reading Neural Turing Machines
CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy
CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy - Downlin et al. 2016 Fixed misspellings of homomorphic ! With the rise of machine learning, it's easy to imagine all sorts of cloud services that can process your data and make predictions of some kind (Machine Learning as a Service - MLAS). … Continue reading CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy
Trajectory Data Mining: An Overview
Trajectory Data Mining: An Overview - Zheng 2015 In 'Trajectory Data Mining,' Zheng conducts a high-level tour of the techniques involved in working with trajectory data. This is the data created by a moving object, as a sequence of locations, often with uncertainty around the exact location at each point. This could be GPS trajectories … Continue reading Trajectory Data Mining: An Overview
Google’s Hybrid Approach to Research
Google's Hybrid Approach to Research - Spector et al. 2012 Something a little different to close out the week, a paper describing how Google conduct research. It's a fascinating look at how they balance fundamental and applied research, how they integrate research into product teams, and how they measure the contribution of the research. I … Continue reading Google’s Hybrid Approach to Research
the morning paper 