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COIN: COmpression with Implicit Neural representations., , , , and . CoRR, (2021)COIN++: Data Agnostic Neural Compression., , , , , and . CoRR, (2022)Performance Evaluation of Quality of Service for Joint Packet Dropping and Scheduling., , , and . Wireless Personal Communications, 83 (2): 1549-1566 (2015)Gradient \$\textbackslashell\_1\$ Regularization for Quantization Robustness, , , , , and . International Conference on Learning Representations, (2020)An Empirical study of Binary Neural Networks' Optimisation., , , and . ICLR (Poster), OpenReview.net, (2019)COIN++: Neural Compression Across Modalities., , , , , and . Trans. Mach. Learn. Res., (2022)Gradient $\ell_1$ Regularization for Quantization Robustness., , , , , and . ICLR, OpenReview.net, (2020)Single Shot Structured Pruning Before Training., , , , and . CoRR, (2020)Using Pre-trained Full-Precision Models to Speed Up Training Binary Networks For Mobile Devices., and . MobiSys, page 528. ACM, (2018)Compression of models and data in deep learning.. University of Oxford, UK, (2022)British Library, EThOS.