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Neural Architecture Search using Deep Neural Networks and Monte Carlo Tree Search

, , , , and . (2018)cite arxiv:1805.07440Comment: To appear in the Thirty-Fourth AAAI conference on Artificial Intelligence (AAAI-2020).

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Learning Compact Recurrent Neural Networks with Block-Term Tensor Decomposition., , , , , , and . CoRR, (2017)SuperNeurons: FFT-based Gradient Sparsification in the Distributed Training of Deep Neural Networks., , , , , , , , and . CoRR, (2018)Neural Architecture Search Using Deep Neural Networks and Monte Carlo Tree Search., , , , and . AAAI, page 9983-9991. AAAI Press, (2020)AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search., , and . CoRR, (2018)Sample-Efficient Neural Architecture Search by Learning Action Space., , , , and . CoRR, (2019)Sample-Efficient Neural Architecture Search by Learning Actions for Monte Carlo Tree Search., , , , and . IEEE Trans. Pattern Anal. Mach. Intell., 44 (9): 5503-5515 (2022)Building an Intelligent Agent to Design Neural Networks.. Brown University, USA, (2022)FFT-based Gradient Sparsification for the Distributed Training of Deep Neural Networks., , , , , , and . HPDC, page 113-124. ACM, (2020)GPUNet: Searching the Deployable Convolution Neural Networks for GPUs., , , , , and . CoRR, (2022)Efficient Communications in Training Large Scale Neural Networks., , , , , , , and . ACM Multimedia (Thematic Workshops), page 110-116. ACM, (2017)