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Model-Free Surrogate-Assisted Neural Architecture Search for Evolving Variable-Length Dense Blocks
Neural Architecture Search (NAS) has emerged as a powerful paradigm for automatically designing deep neural networks; however, its practical adoption is often limited by substantial computational cost. To alleviate expensive full-training evaluations, surrogate-based methods have been introduced to
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