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Models/IS-DARTS

IS-DARTS

Reported on 12 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.

Methodology12 results

  • Neural Architecture SearchonNAS-Bench-201, ImageNet-16-120
    Accuracy (Test)· 2023-12-19
    46.34
    best: 46.98 (CR-LSO)
    IS-DARTS: Stabilizing DARTS through Precise Measurement on Candidate ImportancearXiv:2312.12648
  • Neural Architecture SearchonNAS-Bench-201, ImageNet-16-120
    Accuracy (Val)· 2023-12-19
    46.37
    best: 46.73 (AG-Net)
    IS-DARTS: Stabilizing DARTS through Precise Measurement on Candidate ImportancearXiv:2312.12648
  • Neural Architecture SearchonNAS-Bench-201, CIFAR-10
    Accuracy (Test)· 2023-12-19
    94.36
    best: 94.37 (DiNAS)
    IS-DARTS: Stabilizing DARTS through Precise Measurement on Candidate ImportancearXiv:2312.12648
  • Neural Architecture SearchonNAS-Bench-201, CIFAR-10
    Accuracy (Val)· 2023-12-19
    91.55
    best: 91.61 (DiNAS)
    IS-DARTS: Stabilizing DARTS through Precise Measurement on Candidate ImportancearXiv:2312.12648
  • Neural Architecture SearchonNAS-Bench-201, CIFAR-100
    Accuracy (Test)· 2023-12-19
    73.51
    IS-DARTS: Stabilizing DARTS through Precise Measurement on Candidate ImportancearXiv:2312.12648
  • Neural Architecture SearchonNAS-Bench-201, CIFAR-100
    Accuracy (Val)· 2023-12-19
    73.49
    IS-DARTS: Stabilizing DARTS through Precise Measurement on Candidate ImportancearXiv:2312.12648
  • AutoMLonNAS-Bench-201, ImageNet-16-120
    Accuracy (Test)· 2023-12-19
    46.34
    best: 46.98 (CR-LSO)
    IS-DARTS: Stabilizing DARTS through Precise Measurement on Candidate ImportancearXiv:2312.12648
  • AutoMLonNAS-Bench-201, ImageNet-16-120
    Accuracy (Val)· 2023-12-19
    46.37
    best: 46.73 (AG-Net)
    IS-DARTS: Stabilizing DARTS through Precise Measurement on Candidate ImportancearXiv:2312.12648
  • AutoMLonNAS-Bench-201, CIFAR-10
    Accuracy (Test)· 2023-12-19
    94.36
    best: 94.37 (DiNAS)
    IS-DARTS: Stabilizing DARTS through Precise Measurement on Candidate ImportancearXiv:2312.12648
  • AutoMLonNAS-Bench-201, CIFAR-10
    Accuracy (Val)· 2023-12-19
    91.55
    best: 91.61 (DiNAS)
    IS-DARTS: Stabilizing DARTS through Precise Measurement on Candidate ImportancearXiv:2312.12648
  • AutoMLonNAS-Bench-201, CIFAR-100
    Accuracy (Test)· 2023-12-19
    73.51
    IS-DARTS: Stabilizing DARTS through Precise Measurement on Candidate ImportancearXiv:2312.12648
  • AutoMLonNAS-Bench-201, CIFAR-100
    Accuracy (Val)· 2023-12-19
    73.49
    IS-DARTS: Stabilizing DARTS through Precise Measurement on Candidate ImportancearXiv:2312.12648