3 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.DC2023★ 3 cited
The AutoSPADA Platform: User-Friendly Edge Computing for Distributed Learning and Data Analytics in Connected Vehicles
Adrian Nilsson, Simon Smith, Jonas Hagmar +2
Contemporary connected vehicles host numerous applications, such as diagnostics and navigation, and new software is continuously being developed. However, the development process t…
cs.DS2019★ 2 cited
S-RASTER: Contraction Clustering for Evolving Data Streams
Gregor Ulm, Simon Smith, Adrian Nilsson +2
Contraction Clustering (RASTER) is a single-pass algorithm for density-based clustering of 2D data. It can process arbitrary amounts of data in linear time and in constant memory,…
cs.DS2019
Contraction Clustering (RASTER): A Very Fast Big Data Algorithm for Sequential and Parallel Density-Based Clustering in Linear Time, Constant Memory, and a Single Pass
Gregor Ulm, Simon Smith, Adrian Nilsson +2
Clustering is an essential data mining tool for analyzing and grouping similar objects. In big data applications, however, many clustering algorithms are infeasible due to their hi…