Learning certifiably optimal rule lists for categorical data

October 30, 2019May 25, 2020 ~ Adrian Colyer ~ 5 Comments

Learning certifiably optimal rule lists for categorical data Angelino et al., JMLR 2018 Today we’re taking a closer look at CORELS, the Certifiably Optimal RulE ListS algorithm that we encountered in Rudin’s arguments for interpretable models earlier this week. We’ve been able to create rule lists (decision trees) for a long time, e.g. using CART, ... Continue Reading

Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead

October 28, 2019May 25, 2020 ~ Adrian Colyer ~ 10 Comments

Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead Rudin et al., arXiv 2019 With thanks to Glyn Normington for pointing out this paper to me. It’s pretty clear from the title alone what Cynthia Rudin would like us to do! The paper is a mix of technical ... Continue Reading

Task-based effectiveness of basic visualizations

October 25, 2019May 25, 2020 ~ Adrian Colyer ~ 12 Comments

Task-based effectiveness of basic visualizations Saket et al., IEEE Transactions on Visualization and Computer Graphics 2019 So far this week we’ve seen how to create all sorts of fantastic interactive visualisations, and taken a look at what data analysts actually do when they do ‘exploratory data analysis.’ To round off the week today’s choice is ... Continue Reading

Futzing and moseying: interviews with professional data analysts on exploration practices

October 23, 2019May 25, 2020 ~ Adrian Colyer ~ 1 Comment

Futzing and moseying: interviews with professional data analysts on exploration practices Alspaugh et al., VAST'18 What do people actually do when they do ‘exploratory data analysis’ (EDA)? This 2018 paper reports on the findings from interviews with 30 professional data analysts to see what they get up to in practice. The only caveat to the ... Continue Reading

Vega-Lite: a grammar of interactive graphics

October 21, 2019May 25, 2020 ~ Adrian Colyer ~ 2 Comments

Vega-lite: a grammar of interactive graphics Satyanarayan et al., IEEE transactions on visualization and computer graphics, 2016 From time to time I receive a request for more HCI (human-computer interaction) related papers in The Morning Paper. If you’ve been a follower of The Morning Paper for any time at all you can probably tell that ... Continue Reading

HackPPL: a universal probabilistic programming language

October 18, 2019May 25, 2020 ~ Adrian Colyer ~ 28 Comments

HackPPL: a universal probabilistic programming language Ai et al., MAPL'19 The Hack programming language, as the authors proudly tell us, is "a dominant web development language across large technology firms with over 100 million lines of production code." Nail that niche! Does your market get any smaller if we also require those firms to have ... Continue Reading

“I was told to buy a software or lose my computer: I ignored it.” A study of ransomware

October 16, 2019May 25, 2020 ~ Adrian Colyer ~ 28 Comments

"I was told to buy a software or lose my computer. I ignored it": a study of ransomware Simoiu et al., SOUPS 2019 This is a very easy to digest paper shedding light on the prevalence of ransomware and the characteristics of those most likely to be vulnerable to it. The data comes from a ... Continue Reading

Invisible mask: practical attacks on face recognition with infrared

October 15, 2019May 25, 2020 ~ Adrian Colyer ~ Leave a comment

Invisible mask: practical attacks on face recognition with infrared Zhou et al., arXiv’18 You might have seen selected write-ups from The Morning Paper appearing in ACM Queue. The editorial board there are also kind enough to send me paper recommendations when they come across something that sparks their interest. So this week things are going ... Continue Reading

Learning a unified embedding for visual search at Pinterest

October 11, 2019May 25, 2020 ~ Adrian Colyer ~ 2 Comments

Learning a unified embedding for visual search at Pinterest Zhai et al., KDD'19 Last time out we looked at some great lessons from Airbnb as they introduced deep learning into their search system. Today’s paper choice highlights an organisation that has been deploying multiple deep learning models in search (visual search) for a while: Pinterest. ... Continue Reading

Applying deep learning to Airbnb search

October 9, 2019May 25, 2020 ~ Adrian Colyer ~ 16 Comments

Applying deep learning to Airbnb search Haldar et al., KDD'19 Last time out we looked at Booking.com’s lessons learned from introducing machine learning to their product stack. Today’s paper takes a look at what happened in Airbnb when they moved from standard machine learning approaches to deep learning. It’s written in a very approachable style ... Continue Reading

the morning paper

a random walk through Computer Science research, by Adrian Colyer
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