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Speedy greedy feature selection: better redshift estimation via massive parallelism
Fabian Cristian Gieseke
, Kai Lars Polsterer,
Cosmin Eugen Oancea
,
Christian Igel
Datalogisk Institut
7
Citationer (Scopus)
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Keyphrases
Massive Parallelism
100%
Greedy Feature Selection
100%
Astronomy
100%
K-nearest Neighbor Model
100%
Order of Magnitude
50%
Feature Selection
50%
Informative Features
50%
Parallel Implementation
50%
Machine Learning
50%
Overall Scheme
50%
Graphics Processing Unit
50%
Incremental Feature Selection
50%
Distant Galaxies
50%
Task Dependency
50%
Computational Speed
50%
Challenging Tasks
50%
Computer Science
Parallelism
100%
Feature Selection
100%
Feature Extraction
100%
Machine Learning
33%
Learning System
33%
Graphics Processing Unit
33%
Parallel Implementation
33%
Physics
Machine Learning
100%