Researchers have developed a new method called Online Conformal Calibration (OCC) to improve the efficiency of hardware-aware neural architecture search (NAS). Traditional NAS methods are costly because they require training every architecture to evaluate its performance. OCC, an extension of conformal prediction, uses adaptive feedback control to maintain a desired level of coverage, ensuring that a specified fraction of candidate architectures are not wrongly discarded. This approach significantly reduces the number of evaluations needed, pruning 25-50% of candidates without sacrificing accuracy, and offers better control over coverage compared to static methods or Gaussian process baselines. AI
IMPACT Improves efficiency in neural architecture search by reducing computational cost without sacrificing accuracy.
RANK_REASON Academic paper detailing a novel method for neural architecture search. [lever_c_demoted from research: ic=1 ai=1.0]
- Adaptive Conformal Inference
- alphaXiv
- arXiv
- CatalyzeX
- Conformal prediction
- DagsHub
- Gaussian process
- Gotit.pub
- Hugging Face
- IArxiv
- RL-Driven Hardware-Aware NAS
- ScienceCast
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