4 papers
Spatial-Spectral Adaptive Fidelity and Noise Prior Reduction Guided Hyperspectral Image Denoising
Xuelin Xie, Xiliang Lu, Zhengshan Wang +2
The core challenge of hyperspectral image denoising is striking the right balance between data fidelity and noise prior modeling. Most existing methods place too much emphasis on t…
Online Quantum State Tomography via Stochastic Gradient Descent
Jian-Feng Cai, Yuling Jiao, Yinan Li +3
We initiate the study of online quantum state tomography (QST), where the matrix representation of an unknown quantum state is reconstructed by sequentially performing a batch of m…
Accelerating Ill-conditioned Hankel Matrix Recovery via Structured Newton-like Descent
HanQin Cai, Longxiu Huang, Xiliang Lu +1
This paper studies the robust Hankel recovery problem, which simultaneously removes the sparse outliers and fulfills missing entries from the partial observation. We propose a nove…
GraHTP: A Provable Newton-like Algorithm for Sparse Phase Retrieval
Licheng Dai, Xiliang Lu, Juntao You
This paper investigates the sparse phase retrieval problem, which aims to recover a sparse signal from a system of quadratic measurements. In this work, we propose a novel non-conv…