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Compressed Sensing With Side Information: Geometrical Interpretation and Performance Bounds.

, , and . CoRR, (2014)

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Bayesian Compressed Sensing with Heterogeneous Side Information., , , and . DCC, page 191-200. IEEE, (2016)Reference-based compressed sensing: A sample complexity approach., , , , and . ICASSP, page 4687-4691. IEEE, (2016)Progressive Deep Image Compression for Hybrid Contexts of Image Classification and Reconstruction., , , , , and . IEEE J. Sel. Areas Commun., 41 (1): 72-89 (2023)Measurement-Consistent Networks via a Deep Implicit Layer for Solving Inverse Problems., and . CoRR, (2022)The Rate-Distortion-Perception-Classification Tradeoff: Joint Source Coding and Modulation via Inverse-Domain GANs., , , , and . CoRR, (2023)Overcoming Measurement Inconsistency in Deep Learning for Linear Inverse Problems: Applications in Medical Imaging., and . CoRR, (2020)Sharper Bounds for Proximal Gradient Algorithms with Errors., , , and . CoRR, (2022)Multimodal Image Super-Resolution via Joint Sparse Representations Induced by Coupled Dictionaries., , , , , and . IEEE Trans. Computational Imaging, (2020)Efficient Reconfigurable Mixed Precision ℓ 1 Solver for Compressive Depth Reconstruction., , , , and . J. Signal Process. Syst., 94 (10): 1083-1099 (2022)Overcoming Measurement Inconsistency In Deep Learning For Linear Inverse Problems: Applications In Medical Imaging., and . ICASSP, page 8113-8117. IEEE, (2021)