Papers › DARTS-PRIME: Regularization and Scheduling Improve Constrained Optimization in...
DARTS-PRIME: Regularization and Scheduling Improve Constrained Optimization in Differentiable NAS
Kaitlin Maile, Erwan Lecarpentier, Hervé Luga, Dennis G. Wilson
Differentiable Architecture Search (DARTS) is a recent neural architecture search (NAS) method based on a differentiable relaxation. Due to its success, numerous variants analyzing and improving parts of the DARTS framework have recently been proposed. By considering the problem as a constrained bilevel optimization, we present and analyze DARTS-PRIME, a variant including improvements to architectural weight update scheduling and regularization towards discretization. We propose a dynamic schedule based on per-minibatch network information to make architecture updates more informed, as well as proximity regularization to promote well-separated discretization. Our results in multiple domains show that DARTS-PRIME improves both performance and reliability, comparable to state-of-the-art in differentiable NAS.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Neural Architecture Search | CIFAR-10 | DARTS-PRIME | Parameters | 3.7M | #29 of 41 | Archive leaderboard | report |
| Neural Architecture Search | CIFAR-10 | DARTS-PRIME | Search Time (GPU days) | 0.5 | #29 of 41 | Archive leaderboard | report |
| Neural Architecture Search | CIFAR-10 | DARTS-PRIME | Top-1 Error Rate | 2.62% | #29 of 41 | Archive leaderboard | report |
| Neural Architecture Search | CIFAR-100 | DARTS-PRIME | PARAMS | 3.16M | #10 of 13 | Archive leaderboard | report |
| Neural Architecture Search | CIFAR-100 | DARTS-PRIME | Percentage Error | 17.44 | #10 of 13 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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