TNAS

Reported on 6 benchmarks across 2 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology6 results

Neural Architecture SearchonNAS-Bench-201, ImageNet-16-120
Accuracy (Test)· 2022-04-11
46.31
best: 46.98 (CR-LSO)
When NAS Meets Trees: An Efficient Algorithm for Neural Architecture Search arXiv:2204.04918
Neural Architecture SearchonNAS-Bench-201, CIFAR-10
Accuracy (Test)· 2022-04-11
94.35
best: 94.37 (DiNAS)
When NAS Meets Trees: An Efficient Algorithm for Neural Architecture Search arXiv:2204.04918
Neural Architecture SearchonNAS-Bench-201, CIFAR-100
Accuracy (Test)· 2022-04-11
73.02
best: 73.51 (DiNAS)
When NAS Meets Trees: An Efficient Algorithm for Neural Architecture Search arXiv:2204.04918
AutoMLonNAS-Bench-201, ImageNet-16-120
Accuracy (Test)· 2022-04-11
46.31
best: 46.98 (CR-LSO)
When NAS Meets Trees: An Efficient Algorithm for Neural Architecture Search arXiv:2204.04918
AutoMLonNAS-Bench-201, CIFAR-10
Accuracy (Test)· 2022-04-11
94.35
best: 94.37 (DiNAS)
When NAS Meets Trees: An Efficient Algorithm for Neural Architecture Search arXiv:2204.04918
AutoMLonNAS-Bench-201, CIFAR-100
Accuracy (Test)· 2022-04-11
73.02
best: 73.51 (DiNAS)
When NAS Meets Trees: An Efficient Algorithm for Neural Architecture Search arXiv:2204.04918