47 citations · 82 across the 7 of their papers we have counts for
7 papers
ConvBoost: Boosting ConvNets for Sensor-based Activity Recognition
Shuai Shao, Yu Guan, Bing Zhai +2
Human activity recognition (HAR) is one of the core research themes in ubiquitous and wearable computing. With the shift to deep learning (DL) based analysis approaches, it has bec…
Benchmark time series data sets for PyTorch -- the torchtime package
Philip Darke, Paolo Missier, Jaume Bacardit
The development of models for Electronic Health Record data is an area of active research featuring a small number of public benchmark data sets. Researchers typically write custom…
Preserving the value of large scale data analytics over time through selective re-computation
Paolo Missier, Jacek Cala, Maisha Rathi
A pervasive problem in Data Science is that the knowledge generated by possibly expensive analytics processes is subject to decay over time, as the data used to compute it drifts,…
Measuring the impact of cognitive distractions on driving performance using time series analysis
Matias Garcia-Constantino, Paolo Missier, Phil Blytheand Amy Weihong Guo
Using current sensing technology, a wealth of data on driving sessions is potentially available through a combination of vehicle sensors and drivers' physiology sensors (heart rate…
ProvGen: generating synthetic PROV graphs with predictable structure
Hugo Firth, Paolo Missier
This paper introduces provGen, a generator aimed at producing large synthetic provenance graphs with predictable properties and of arbitrary size. Synthetic provenance graphs serve…
ProvAbs: model, policy, and tooling for abstracting PROV graphs
Paolo Missier, Jeremy Bryans, Carl Gamble +2
Provenance metadata can be valuable in data sharing settings, where it can be used to help data consumers form judgements regarding the reliability of the data produced by third pa…