Tackling Diverse Tasks with Neural Architecture Search

DASH searches for the optimal kernel size and dilation rate efficiently from a large set of options for each convolutional layer in a CNN backbone. The resulting model can achieve task-specific feature extraction and work as well as hand-designed expert architectures, making DASH an effective tool for tackling diverse tasks beyond well-researched domains like vision. The past decade has witnessed the success of machine learning (ML) in solving diverse real-world problems, from facial recognition and machine translation to disease diagnosis …

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