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Bayesian Compressed Sensing with Heterogeneous Side Information., , , и . DCC, стр. 191-200. IEEE, (2016)Reference-based compressed sensing: A sample complexity approach., , , , и . ICASSP, стр. 4687-4691. IEEE, (2016)Deep Coupled-Representation Learning for Sparse Linear Inverse Problems With Side Information., и . IEEE Signal Process. Lett., 26 (12): 1768-1772 (2019)Learned Gradient Compression for Distributed Deep Learning., , , и . IEEE Trans. Neural Networks Learn. Syst., 33 (12): 7330-7344 (2022)Maximum Likelihood Laplacian Correlation Channel Estimation in Layered Wyner-Ziv Coding., , , , и . IEEE Trans. Signal Process., 62 (4): 892-904 (2014)Representation Learning with Information Theory for COVID-19 Detection., , , , и . CoRR, (2022)Efficient hash-driven Wyner-Ziv video coding for visual sensors., , , , , , , и . ICDSC, стр. 1-6. IEEE, (2011)Achievability of the rate-distortion function in binary uniform source coding with side information., , , и . ICT, стр. 1-5. IEEE, (2016)Dynamic sparse state estimation using ℓ1-ℓ1 minimization: Adaptive-rate measurement bounds, algorithms and applications., , , , и . ICASSP, стр. 3332-3336. IEEE, (2015)The Rate Loss in Binary Source Coding with Decoder Side Information., , , и . DCC, стр. 633. IEEE, (2016)