Presentation
Poster 33: Enhancing Neural Architecture Search with Speciation and Inter-Epoch Crossover
Event Type
ACM Student Research Competition: Graduate Posters
ACM Student Research Competition: Undergraduate Posters
Posters
TP
EX
EXH
Student Program
TimeThursday, 21 November 20198:30am - 5pm
LocationE Concourse
DescriptionAs deep learning continues to expand into new areas of application, the demand for efficient use of our HPC resources increase. For new problem domains, new model architectures are developed through a neural architecture search (NAS), which consist of iteratively training many neural networks. To combat the computational waste and maximize compute efficiency for NAS, we demonstrate that the use of genetic algorithms with speciation can be used to both shorten training time and increase accuracy at each iteration.
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