Yesterday we looked at a series of papers on DNN understanding, generalisation, and transfer learning. One additional way of understanding what's going on inside a network is to understand what can break it. Adversarial examples are deliberately constructed inputs which cause a network to produce the wrong outputs (e.g., misclassify an input image). We'll start … Continue reading When DNNs go wrong – adversarial examples and what we can learn from them
Month: February 2017
Understanding, generalisation, and transfer learning in deep neural networks
This is the first in a series of posts looking at the 'top 100 awesome deep learning papers.' Deviating from the normal one-paper-per-day format, I'll take the papers mostly in their groupings as found in the list (with some subdivision, plus a few extras thrown in) - thus we'll be looking at multiple papers each … Continue reading Understanding, generalisation, and transfer learning in deep neural networks
An experiment with awesome deep learning papers
There have been several lists of deep learning papers doing the rounds. Recently Terry Taewoong Um's list of the top 100 awesome and most cited deep learning papers caught my eye. Deep learning is an exciting area and it's moving fast. I'd like to know what's in those 100 papers (thankfully, we have at least … Continue reading An experiment with awesome deep learning papers
On decentralizing prediction markets and order books
On decentralizing prediction markets and order books Clark et al., 13th Annual Workshop on the Economics of Information Security, 2014 This is the last of five papers in the ACM Queue Research for Practice series on 'Cryptocurrencies, Blockchains, and Smart Contracts .' It serves as a good example of repurposing block chains as a foundation … Continue reading On decentralizing prediction markets and order books
Making smart contracts smarter
Making smart contracts smarter Luu et al., CCS 2016 This is the fourth in a series of papers from the ACM Queue Research for Practice 'Cryptocurrencies, Blockchains and Smart Contracts' selections, in which Luu at al. look at smart contracts in Ethereum. Smart contracts are a really intriguing idea and have generated a lot of … Continue reading Making smart contracts smarter
A first look at the usabilty of Bitcoin key management
A first look at the usability of Bitcoin key management Eskandari et al., USEC 2015 This is the third of five papers from the ACM Queue Research for Practice selections on 'Cryptocurrencies, Blockchains, and Smart Contracts.' And thankfully it's much easier to read and understand than yesterdays! The authors point out that a cryptocurrency intended … Continue reading A first look at the usabilty of Bitcoin key management
Zerocash: Decentralized anonymous payments from Bitcoin
Zerocash: Decentralized anonymous payments from Bitcoin Ben-Sasson et al., 2014 Yesterday we saw that de-anonymising techniques can learn a lot about the true identities of participants in Bitcoin transactions. Ben-Sasson et al. point out that given this, Bitcoin could be considered significantly less private than traditional schemes: While users may employ many identities (or pseudonyms) … Continue reading Zerocash: Decentralized anonymous payments from Bitcoin
A fistful of Bitcoins: Characterizing payments among men with no names
A fistful of bitcoins: characterizing payments among men with no names Meiklejohn et al., USENIX ;login: 2013 This week we're going to be looking at the five papers from the ACM Queue Research for Practice selections on 'Cryptocurrencies, Blockchains, and Smart Contracts.' These papers are chosen by Arvind Narayanan and Andrew Miller, co-authors of the … Continue reading A fistful of Bitcoins: Characterizing payments among men with no names
Online actions with offline impact: how online social networks influence online and offline social behavior
Online actions with offline impact: how online social networks influence online and offline user behavior Althoff et al., WSDM 2017 You can go to a lot of effort to build social networking features or support into your app or website. If the goal is engagement directly within the app then at least you have something … Continue reading Online actions with offline impact: how online social networks influence online and offline social behavior
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
the morning paper 