BN-NAS: Neural Architecture Search with Batch Normalization

2021/08/16 by Boyu Chen, Peixia Li, Chen, Boyu +13 · 1 citation
Computer Science · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences

paper · pdf · doi:10.48550/arxiv.2108.07375

openalex publication_date 2021/08/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We present BN-NAS, neural architecture search with Batch Normalization (BN-NAS), to accelerate neural architecture search (NAS). BN-NAS can significantly reduce the time required by model training and evaluation in NAS. Specifically, for fast evaluation, we propose a BN-based indicator for predicting subnet performance at a very early training stage. The BN-based indicator further facilitates us to improve the training efficiency by only training the BN parameters during the supernet training. This is based on our observation that training the whole supernet is not necessary while training only BN parameters accelerates network convergence for network architecture search. Extensive experiments show that our method can significantly shorten the time of training supernet by more than 10 times and shorten the time of evaluating subnets by more than 600,000 times without losing accuracy.

Citations

• Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
• Learning Efficient Convolutional Networks through Network Slimming
• Efficient Neural Architecture Search via Parameter Sharing
• DARTS: Differentiable Architecture Search
• Searching for Efficient Multi-Scale Architectures for Dense Image Prediction
• Drawing Early-Bird Tickets: Towards More Efficient Training of Deep Networks
• FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions
• EfficientDet: Scalable and Efficient Object Detection
• Learning Multiple Layers of Features from Tiny Images

Cited by

• Dextr: Zero-Shot Neural Architecture Search with Singular Value Decomposition and Extrinsic Curvature

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