MOTE-NAS: Multi-Objective Training-based Estimate for Efficient Neural Architecture Search Y u-Ming Zhang 1 Jun-Wei Hsieh

Neural Information Processing Systems 

Neural Architecture Search (NAS) methods seek effective optimization toward performance metrics regarding model accuracy and generalization while facing challenges regarding search costs and GPU resources.

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