Choosing a cloud DBMS: architectures and tradeoffs Tan et al., VLDB'19 If you’re moving an OLAP workload to the cloud (AWS in the context of this paper), what DBMS setup should you go with? There’s a broad set of choices including where you store the data, whether you run your own DBMS nodes or use … Continue reading Choosing a cloud DBMS: architectures and tradeoffs
Month: August 2019
Interactive checks for coordination avoidance
Interactive checks for coordination avoidance Whittaker & Hellerstein et al., VLDB'19 I am so pleased to see a database systems paper addressing the concerns of the application developer! To the developer, a strongly consistent system behaves exactly like a single-threaded system running on a single node, so reasoning about the behaviour of the system is … Continue reading Interactive checks for coordination avoidance
Snuba: automating weak supervision to label training data
Snuba: automating weak supervision to label training data Varma & Ré, VLDB 2019 This week we’re moving on from ICML to start looking at some of the papers from VLDB 2019. VLDB is a huge conference, and once again I have a problem because my shortlist of "that looks really interesting, I’d love to read … Continue reading Snuba: automating weak supervision to label training data
Learning to prove theorems via interacting with proof assistants
Learning to prove theorems via interacting with proof assistants Yang & Deng, ICML'19 Something a little different to end the week: deep learning meets theorem proving! It’s been a while since we gave formal methods some love on The Morning Paper, and this paper piqued my interest. You’ve probably heard of Coq, a proof management … Continue reading Learning to prove theorems via interacting with proof assistants
Statistical foundations of virtual democracy
Statiscal foundations of virtual democracy Kahng et al., ICML'19 This is another paper on the theme of combining information and making decisions in the face of noise and uncertainty - but the setting is quite different to those we’ve been looking at recently. Consider a food bank that receives donations of food and distributes it … Continue reading Statistical foundations of virtual democracy
Robust learning from untrusted sources
Robust learning from untrusted sources Konstantinov & Lampert, ICML'19 Welcome back to a new term of The Morning Paper! Just before the break we were looking at selected papers from ICML’19, including “Data Shapley.” I’m going to pick things up pretty much where we left off with a few more ICML papers... Data Shapley provides … Continue reading Robust learning from untrusted sources
the morning paper 