activity
20162022
most citedSpectral Compressed Sensing via Projected Gradient Descent

3 citations · 4 across the 4 of their papers we have counts for

collaborators

8 papers

eess.IV2021

Image Deraining and Denoising Convolutional Neural Network ForAutonomous Driving

Kaige Wang, Long Chen, TIanming Wang +3

Perception plays an important role in reliable decision-making for autonomous vehicles. Over the last ten years, huge advances have been made in the field of perception. However, p…

cs.IT2019

Accelerated Structured Alternating Projections for Robust Spectrally Sparse Signal Recovery

HanQin Cai, Jian-Feng Cai, Tianming Wang +1

Consider a spectrally sparse signal that consists of complex sinusoids with or without damping. We study the robust recovery problem for the spectrally sparse…

math.NA2019

SketchyCoreSVD: SketchySVD from Random Subsampling of the Data Matrix

Chandrajit Bajaj, Yi Wang, Tianming Wang

We present a method called SketchyCoreSVD to compute the near-optimal rank r SVD of a data matrix by building random sketches only from its subsampled columns and rows. We provide…

math.NA2019

Fast Cadzow's Algorithm and a Gradient Variant

Haifeng Wang, Jian-Feng Cai, Tianming Wang +1

The Cadzow's algorithm is a signal denoising and recovery method which was designed for signals corresponding to low rank Hankel matrices. In this paper we first introduce a Fast C…

cs.CV20191 cited

Blind Hyperspectral-Multispectral Image Fusion via Graph Laplacian Regularization

Chandrajit Bajaj, Tianming Wang

Fusing a low-resolution hyperspectral image (HSI) and a high-resolution multispectral image (MSI) of the same scene leads to a super-resolution image (SRI), which is information ri…

cs.IT2018

Outlier Detection using Generative Models with Theoretical Performance Guarantees

Jirong Yi, Anh Duc Le, Tianming Wang +2

This paper considers the problem of recovering signals from compressed measurements contaminated with sparse outliers, which has arisen in many applications. In this paper, we prop…