12 citations · 25 across the 6 of their papers we have counts for
7 papers
Incremental Column Subset Selection via Conditional Determinantal Point Processes
Laura Grigori, Zhipeng Xue
Column subset selection aims to seek a small set of representative columns that accurately approximates a given matrix. We study this problem from the perspective of determinantal…
Randomized strong rank-revealing QR for column subset selection and low-rank matrix approximation
Laura Grigori, Zhipeng Xue
We discuss a randomized strong rank-revealing QR factorization that effectively reveals the spectrum of a matrix . This factorization can be used to address problems su…
Score-Based Variational Inference for Inverse Problems
Zhipeng Xue, Penghao Cai, Xiaojun Yuan +1
Existing diffusion-based methods for inverse problems sample from the posterior using score functions and accept the generated random samples as solutions. In applications that pos…
Denoising-based Turbo Message Passing for Compressed Video Background Subtraction
Zhipeng Xue, Xiaojun Yuan, Yang Yang
In this paper, we consider the compressed video background subtraction problem that separates the background and foreground of a video from its compressed measurements. The backgro…
TARM: A Turbo-type Algorithm for Affine Rank Minimization
Zhipeng Xue, Xiaojun Yuan, Junjie Ma +1
The affine rank minimization (ARM) problem arises in many real-world applications. The goal is to recover a low-rank matrix from a small amount of noisy affine measurements. The or…
Denoising-based Turbo Compressed Sensing
Zhipeng Xue, Junjie Ma, Xiaojun Yuan
Turbo compressed sensing (Turbo-CS) is an efficient iterative algorithm for sparse signal recovery with partial orthogonal sensing matrices. In this paper, we extend the Turbo-CS a…
D-OAMP: A Denoising-based Signal Recovery Algorithm for Compressed Sensing
Zhipeng Xue, Junjie Ma, Xiaojun Yuan
Approximate message passing (AMP) is an efficient iterative signal recovery algorithm for compressed sensing (CS). For sensing matrices with independent and identically distributed…