5 citations · 11 across the 6 of their papers we have counts for
6 papers
PANDAS: Peer-to-peer, Adaptive Networking for Data Availability Sampling within Ethereum Consensus Timebounds
Matthieu Pigaglio, Onur Ascigil, Michał Król +6
Layer-2 protocols can assist Ethereum's limited throughput, but globally broadcasting layer-2 data limits their scalability. The Danksharding evolution of Ethereum aims to support…
When to Accept Automated Predictions and When to Defer to Human Judgment?
Daniel Sikar, Artur Garcez, Tillman Weyde +2
Ensuring the reliability and safety of automated decision-making is crucial. It is well-known that data distribution shifts in machine learning can produce unreliable outcomes. Thi…
The Misclassification Likelihood Matrix: Some Classes Are More Likely To Be Misclassified Than Others
Daniel Sikar, Artur Garcez, Robin Bloomfield +6
This study introduces the Misclassification Likelihood Matrix (MLM) as a novel tool for quantifying the reliability of neural network predictions under distribution shifts. The MLM…
A Survey on Experimental Performance Evaluation of Data Distribution Service (DDS) Implementations
Kaleem Peeroo, Peter Popov, Vladimir Stankovic
The Data Distribution Service (DDS) is a widely used communication specification for real-time mission-critical systems that follow the principles of publish-subscribe middleware.…
Data Availability Sampling in Ethereum: Analysis of P2P Networking Requirements
Michał Król, Onur Ascigil, Sergi Rene +6
Despite their increasing popularity, blockchains still suffer from severe scalability limitations. Recently, Ethereum proposed a novel approach to block validation based on Data Av…
Exploring the Effects of Multicast Communication on DDS Performance
Kaleem Peeroo, Peter Popov, Vladimir Stankovic
The Data Distribution Service (DDS) is an Object Management Group (OMG) standard for high-performance and real-time systems. DDS is a data-centric middleware based on the publish-s…