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Auto-Agent-Distiller: Towards Efficient Deep Reinforcement Learning Agents via Neural Architecture Search., , , и . CoRR, (2020)O-HAS: Optical Hardware Accelerator Search for Boosting Both Acceleration Performance and Development Speed., , , , и . ICCAD, стр. 1-9. IEEE, (2021)ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks., , , , и . ICML, том 162 из Proceedings of Machine Learning Research, стр. 25566-25580. PMLR, (2022)DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks., , , , , , , и . ICML, том 162 из Proceedings of Machine Learning Research, стр. 6849-6862. PMLR, (2022)Omni-Recon: Towards General-Purpose Neural Radiance Fields for Versatile 3D Applications., , , , , и . CoRR, (2024)SmartDeal: Remodeling Deep Network Weights for Efficient Inference and Training., , , , , , , , и . IEEE Trans. Neural Networks Learn. Syst., 34 (10): 7099-7113 (октября 2023)Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks., , , , , , , , и . ICLR, OpenReview.net, (2020)Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?, , , , и . ICLR, OpenReview.net, (2022)InstantNet: Automated Generation and Deployment of Instantaneously Switchable-Precision Networks., , , , , , , , и . DAC, стр. 757-762. IEEE, (2021)HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark., , , , , , , , и . CoRR, (2021)