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cs.IT2024
The Error Probability of Spatially Coupled Sparse Regression Codes over Memoryless Channels
Yuhao Liu, Yizhou Xu, Tianqi Hou
Sparse Regression Codes (SPARCs) are capacity-achieving codes introduced for communication over the Additive White Gaussian Noise (AWGN) channels and were later extended to general…
cs.IT2024
Information limits and Thouless-Anderson-Palmer equations for spiked matrix models with structured noise
Jean Barbier, Francesco Camilli, Marco Mondelli +1
We consider a prototypical problem of Bayesian inference for a structured spiked model: a low-rank signal is corrupted by additive noise. While both information-theoretic and algor…
cs.IT2023
Capacity-Achieving Sparse Regression Codes via Vector Approximate Message Passing
Yizhou Xu, YuHao Liu, ShanSuo Liang +4
Sparse regression codes (SPARCs) are a promising coding scheme that can approach the Shannon limit over Additive White Gaussian Noise (AWGN) channels. Previous works have proven th…