40 citations · 51 across the 11 of their papers we have counts for
12 papers
Robust Spectral Recovery for Dynamical Sampling
HanQin Cai, Longxiu Huang, Tianming Wang +1
We study the spectral recovery problem for dynamical sampling on a finite cyclic grid. Given time snapshots obtained from a fixed uniform spatial subsampling of the orbit $x_{\ell}…
Outlier Detection Using Generative Models with Theoretical Performance Guarantees
Jirong Yi, Jingchao Gao, Tianming Wang +2
This paper considers the problem of recovering signals modeled by generative models from linear measurements contaminated with sparse outliers. We propose an outlier detection appr…
Continual Transfer Learning for Cross-Domain Click-Through Rate Prediction at Taobao
Lixin Liu, Yanling Wang, Tianming Wang +6
As one of the largest e-commerce platforms in the world, Taobao's recommendation systems (RSs) serve the demands of shopping for hundreds of millions of customers. Click-Through Ra…
An End-to-End Cascaded Image Deraining and Object Detection Neural Network
Kaige Wang, Tianming Wang, Jianchuang Qu +3
While the deep learning-based image deraining methods have made great progress in recent years, there are two major shortcomings in their application in real-world situations. Firs…
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…
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…
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…
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…
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…
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…
Spectral Compressed Sensing via Projected Gradient Descent
Jian-Feng Cai, Tianming Wang, Ke Wei
Let be a spectrally sparse signal consisting of complex sinusoids with or without damping. We consider the spectral compressed sensing problem, which is abou…
Fast and Provable Algorithms for Spectrally Sparse Signal Reconstruction via Low-Rank Hankel Matrix Completion
Jian-Feng Cai, Tianming Wang, Ke Wei
A spectrally sparse signal of order is a mixture of damped or undamped complex sinusoids. This paper investigates the problem of reconstructing spectrally sparse signals fr…