Abstract
Recently, neural architecture search (NAS) has achieved great success in design neural architectures automatically. Differentiable architecture search (DARTS) has succeeded in reducing computational cost and making the searching process efficient. Based on the cell-based search space in DARTS, we extend the search space by searching diverse cells at different stages and various connection between cells. We also use a progressive and joint method to search the micro and macro architecture together. Extensive experiments on CIFAR-10 demostrate that we can obtain a better result than the original search space.
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