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HALO: Hardware-Aware Learning to Optimize.

, , , , and . ECCV (9), volume 12354 of Lecture Notes in Computer Science, page 500-518. Springer, (2020)

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Auto-Agent-Distiller: Towards Efficient Deep Reinforcement Learning Agents via Neural Architecture Search., , , and . CoRR, (2020)O-HAS: Optical Hardware Accelerator Search for Boosting Both Acceleration Performance and Development Speed., , , , and . ICCAD, page 1-9. IEEE, (2021)Locality Sensitive Teaching., , , , , , and . NeurIPS, page 18049-18062. (2021)ShiftAddNet: A Hardware-Inspired Deep Network., , , , , , , and . NeurIPS, (2020)DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks., , , , , , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 6849-6862. PMLR, (2022)ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks., , , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 25566-25580. PMLR, (2022)Omni-Recon: Towards General-Purpose Neural Radiance Fields for Versatile 3D Applications., , , , , and . CoRR, (2024)SmartDeal: Remodeling Deep Network Weights for Efficient Inference and Training., , , , , , , , and . IEEE Trans. Neural Networks Learn. Syst., 34 (10): 7099-7113 (October 2023)NASA: Neural Architecture Search and Acceleration for Hardware Inspired Hybrid Networks., , , , and . ICCAD, page 58:1-58:9. ACM, (2022)MixRT: Mixed Neural Representations For Real-Time NeRF Rendering., , , and . 3DV, page 1115-1124. IEEE, (2024)