Cong Jin1, Jinjie Huang1,2,*, Yuanjian Chen1, Yuqing Gong1
CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1547-1568, 2024, DOI:10.32604/cmc.2023.047489
Abstract In differentiable search architecture search methods, a more efficient search space design can significantly improve the performance of the searched architecture, thus requiring people to carefully define the search space with different complexity according to various operations. Meanwhile rationalizing the search strategies to explore the well-defined search space will further improve the speed and efficiency of architecture search. With this in mind, we propose a faster and more efficient differentiable architecture search method, AllegroNAS. Firstly, we introduce a more efficient search space enriched by the introduction of two redefined convolution modules. Secondly, we utilize a more efficient architectural parameter regularization… More >
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