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Datasets/NAS-Bench-201

NAS-Bench-201

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NAS-Bench-201 is a benchmark (and search space) for neural architecture search. Each architecture consists of a predefined skeleton with a stack of the searched cell. In this way, architecture search is transformed into the problem of searching a good cell.

Source: NAS-Bench-201: Extending the Scope of Reproducible Neural Architecture Search

Benchmarks

AutoML/Accuracy (%)Neural Architecture Search/Accuracy (%)

Related Benchmarks

NAS-Bench-201, CIFAR-10/AutoML/Accuracy (Test)NAS-Bench-201, CIFAR-10/AutoML/Accuracy (Val)NAS-Bench-201, CIFAR-10/AutoML/Search time (s)NAS-Bench-201, CIFAR-10/Neural Architecture Search/Accuracy (Test)NAS-Bench-201, CIFAR-10/Neural Architecture Search/Accuracy (Val)NAS-Bench-201, CIFAR-10/Neural Architecture Search/Search time (s)NAS-Bench-201, CIFAR-100/AutoML/Accuracy (Test)NAS-Bench-201, CIFAR-100/AutoML/Accuracy (Val)NAS-Bench-201, CIFAR-100/AutoML/Search time (s)NAS-Bench-201, CIFAR-100/Neural Architecture Search/Accuracy (Test)NAS-Bench-201, CIFAR-100/Neural Architecture Search/Accuracy (Val)NAS-Bench-201, CIFAR-100/Neural Architecture Search/Search time (s)NAS-Bench-201, ImageNet-16-120/AutoML/Accuracy (Test)NAS-Bench-201, ImageNet-16-120/AutoML/Accuracy (Val)NAS-Bench-201, ImageNet-16-120/AutoML/Search time (s)NAS-Bench-201, ImageNet-16-120/Neural Architecture Search/Accuracy (Test)NAS-Bench-201, ImageNet-16-120/Neural Architecture Search/Accuracy (Val)NAS-Bench-201, ImageNet-16-120/Neural Architecture Search/Search time (s)

Statistics

Papers
260
Benchmarks
2

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Tasks

AutoMLHyperparameter OptimizationImage ClassificationNeural Architecture Search