具有统一变换的近似消息传递，可实现稳健的双线性恢复（CS IT）---蔡秋纯

最近，已经开发了几种有前途的基于近似消息传递（AMP）的算法，用于模型Y = ∑Kk = 1bkAkC + W的双线性恢复，其中{bk}和C与已知的Ak一起从噪声测量Y中共同恢复。 该问题具有许多应用，例如字典学习，自校准，具有矩阵不确定性的压缩感测等。在这项工作中，我们提出了一种基于AMP的transformation线性双线性恢复算法。 结果表明，与基于最新消息传递的算法相比，所提出的算法更健壮，速度更快，从而显着提高了性能。

原文标题：Approximate Message Passing with Unitary Transformation for Robust Bilinear Recovery

原文：Recently, several promising approximate message passing (AMP) based algorithms have been developed for bilinear recovery with model Y=∑Kk=1bkAkC+W, where {bk} and C are jointly recovered with known Ak from the noisy measurements Y. The bilinear recover problem has many applications such as dictionary learning, self-calibration, compressive sensing with matrix uncertainty, etc. In this work, we propose a new bilinear recovery algorithm based on AMP with unitary transformation. It is shown that, compared to the state-of-the-art message passing based algorithms, the proposed algorithm is much more robust and faster, leading to remarkably better performance.

原文作者：Zhengdao Yuan, Qinghua Guo, Man Luo

原文地址：https://arxiv.org/abs/2005.14132