Search Results - approximate message-passing algorithm~
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Source: The Annals of Probability, 2021 Jan 01. 49(1), 180-205.
Access URL: https://www.jstor.org/stable/27172513
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Authors: et al.
Source: Front Neuroinform
Frontiers in Neuroinformatics, Vol 18 (2024)Subject Terms: ECG, non-local similarity, approximate message passing algorithm, Neurosciences. Biological psychiatry. Neuropsychiatry, weighted nuclear norm minimization, ZZ OA Fund (articles), compressed sensing, RC321-571, Neuroscience
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Source: Proceedings of the 57th Annual ACM Symposium on Theory of Computing. :2237-2248
Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, Statistics - Machine Learning, Computer Science - Data Structures and Algorithms, Data Structures and Algorithms (cs.DS), Machine Learning (stat.ML), Machine Learning (cs.LG)
Access URL: http://arxiv.org/abs/2411.02764
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Source: IEEE Transactions on Information Theory. 70:5811-5856
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Subject Terms: Machine Learning, FOS: Computer and information sciences, Information Theory (cs.IT), Probability (math.PR), Statistics Theory, Information Theory, FOS: Mathematics, Statistics Theory (math.ST), Probability, Machine Learning (cs.LG)
Access URL: http://arxiv.org/abs/2506.23010
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Authors: et al.
Source: IEEE Wireless Communications Letters. 13:1913-1917
Subject Terms: Signal Processing (eess.SP), FOS: Computer and information sciences, Data detection, Computer Science - Information Theory, Information Theory (cs.IT), Detectors, Indexes, Symbols, Graph neural networks, Approximate message passing (AMP), Time-frequency analysis, Orthogonal time frequency space (OTFS) modulation, Message passing, FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Signal Processing, Signal processing algorithms, Graph neural network (GNN)
Access URL: http://arxiv.org/abs/2402.10071
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Source: 2023 IEEE 9th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP). :131-135
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Source: 2023 IEEE 23rd International Conference on Communication Technology (ICCT). :1-5
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Authors: et al.
Source: IEEE Transactions on Signal Processing. 72:3865-3878
Subject Terms: Neurons, Bayesian federated learning, FOS: Computer and information sciences, Turbo deep approximate message passing, Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Expectation maximization, Federated learning, Deep learning, 02 engineering and technology, Bayes methods, Machine Learning (cs.LG), Bayesian deep learning, DNN model compression, Artificial Intelligence (cs.AI), Message passing, 0202 electrical engineering, electronic engineering, information engineering, Training, Signal processing algorithms
Access URL: http://arxiv.org/abs/2402.07366
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Source: The Annals of Applied Probability. 34
Subject Terms: FOS: Computer and information sciences, Computer Science - Information Theory, Information Theory (cs.IT), Probability (math.PR), 0202 electrical engineering, electronic engineering, information engineering, FOS: Mathematics, Mathematics - Statistics Theory, 02 engineering and technology, Statistics Theory (math.ST), 0101 mathematics, 01 natural sciences, Mathematics - Probability
Access URL: http://arxiv.org/abs/2206.13037
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Source: 2023 IEEE Radar Conference (RadarConf23). :1-5
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Authors: et al.
Source: IEEE Access, Vol 7, Pp 9080-9090 (2019)
Subject Terms: iterative thresholding algorithm, Approximate message passing algorithm, nonconvex regularization, sparsity, 0202 electrical engineering, electronic engineering, information engineering, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, 0101 mathematics, 01 natural sciences, variable selection, TK1-9971
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Source: Proceedings of the 56th Annual ACM Symposium on Theory of Computing. :348-357
Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, Statistics - Machine Learning, Computer Science - Data Structures and Algorithms, FOS: Mathematics, Mathematics - Statistics Theory, Data Structures and Algorithms (cs.DS), Machine Learning (stat.ML), Statistics Theory (math.ST), Machine Learning (cs.LG)
Access URL: http://arxiv.org/abs/2311.09017
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Authors: et al.
Source: 2022 2nd International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI). :687-690
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Authors: et al.
Source: IEEE Transactions on Vehicular Technology
Subject Terms: 0203 mechanical engineering, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology
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Source: Skuratovs, N & Davies, M E 2022, ' Compressed Sensing with Upscaled Vector Approximate Message Passing ', IEEE Transactions on Information Theory, vol. 68, no. 7, pp. 4818-4836 . https://doi.org/10.1109/TIT.2022.3157665
IEEE Transactions on Information TheorySubject Terms: Inverse problems, FOS: Computer and information sciences, Covariance matrices, Computer Science - Information Theory, Information Theory (cs.IT), warm-starting, 02 engineering and technology, Tuning, Approximation algorithms, Image reconstruction, expectation propagation, 0202 electrical engineering, electronic engineering, information engineering, Heuristic algorithms, Compressed sensing, conjugate gradient, vector approximate message passing
File Description: application/pdf
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Authors: et al.
Source: 2020 IEEE International Conference on Image Processing (ICIP). :91-95
Subject Terms: Signal Processing (eess.SP), FOS: Computer and information sciences, Computer Science - Information Theory, Information Theory (cs.IT), FOS: Electrical engineering, electronic engineering, information engineering, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Mathematics - Numerical Analysis, Numerical Analysis (math.NA), G.1.3, 02 engineering and technology, Electrical Engineering and Systems Science - Signal Processing
Access URL: http://arxiv.org/pdf/1911.01234
http://arxiv.org/abs/1911.01234
https://arxiv.org/pdf/1911.01234.pdf
https://doi.org/10.1109/ICIP40778.2020.9190668
https://arxiv.org/abs/1911.01234
http://ui.adsabs.harvard.edu/abs/2019arXiv191101234M/abstract
https://dblp.uni-trier.de/db/journals/corr/corr1911.html#abs-1911-01234 -
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Source: Journal of the ACM; Oct2025, Vol. 72 Issue 5, p1-40, 40p
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