The ants and the pheromones
I’m super excited about the new chapter emerging in our research on a programmable cloud. This...
An overview of end-to-end entity resolution for big data
An overview of end-to-end entity resolution for big data, Christophides et al., ACM Computing Surveys, Dec....
Bias in word embeddings
Bias in word embeddings, Papakyriakopoulos et al., FAT*’20 There are no (stochastic) parrots in this paper,...
Seeing is believing: a client-centric specification of database isolation
Seeing is believing: a client-centric specification of database isolation, Crooks et al., PODC’17. Last week we...
Elle: inferring isolation anomalies from experimental observations
Elle: inferring isolation anomalies from experimental observations, Kingsbury & Alvaro, VLDB’20 Is there anything more terrifying,...
Achieving 100Gbps intrusion prevention on a single server
Achieving 100 Gbps intrusion prevention on a single server, Zhao et al., OSDI’20 Papers-we-love is hosting...
Virtual consensus in Delos
Virtual consensus in Delos, Balakrishnan et al. (Facebook, Inc.), OSDI’2020 Before we dive into this paper,...
Helios: hyperscale indexing for the cloud & edge (part II)
Helios: hyperscale indexing for the cloud & edge, Potharaju et al., PVLDB’20 Last time out we...
Helios: hyperscale indexing for the cloud & edge – part 1
Helios: hyperscale indexing for the cloud & edge, Potharaju et al., PVLDB’20 On the surface this...
The case for a learned sorting algorithm
The case for a learned sorting algorithm, Kristo, Vaidya, et al., SIGMOD’20 We’ve watched machine learning...
Firecracker: lightweight virtualization for serverless applications
Firecracker: lightweight virtualisation for serverless applications, Agache et al., NSDI’20 Finally the NSDI’20 papers have opened...
STELLA: report from the SNAFU-catchers workshop on coping with complexity
STELLA: report from the SNAFU-catchers workshop on coping with complexity, Woods 2017, Coping with Complexity workshop...
Synthesizing data structure transformations from input-output examples
Synthesizing data structure transformations from input-output examples, Feser et al., PLDI’15 The Programmatically Interpretable Reinforcement Learning...
Programmatically interpretable reinforcement learning
Programmatically interpretable reinforcement learning, Verma et al., ICML 2018 Being able to trust (interpret, verify) a...
Challenges of real-world reinforcement learning
Challenges of real-world reinforcement learning, Dulac-Arnold et al., ICML’19 Last week we looked at some of...
Ten challenges for making automation a ‘team player’ in joint human-agent activity
Ten challenges for making automation a ‘team player’ in joint human-agent activity, Klein et al., IEEE...
Ironies of automation
Ironies of automation, Bainbridge, Automatica, Vol. 19, No. 6, 1983 With thanks to Thomas Depierre for...
The Year Ahead
Welcome to another year of The Morning Paper! Over the holidays I spent some time mapping...
Benchmarking spreadsheet systems
Benchmarking spreadsheet systems Rahman et al., Preprint A recent TwThread drew my attention to this pre-print...
Declarative assembly of web applications from pre-defined concepts
Declarative assembly of web applications from predefined concepts De Rosso et al., Onward! 2019 I chose...
Efficient lock-free durable sets
Efficient lock-free durable sets Zuriel et al., OOPSLA’19 Given non-volatile memory (NVRAM), the naive hope for...