b'Jian-Feng Cai'

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101 publications
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31 publications

research

∙ 09/05/2023

A Fast and Provable Algorithm for Sparse Phase Retrieval

We study the sparse phase retrieval problem, which aims to recover a spa...

0 Jian-Feng Cai, et al. ∙

research

∙ 09/04/2023

Restoration Guarantee of Image Inpainting via Low Rank Patch Matrix Completion

In recent years, patch-based image restoration approaches have demonstra...

0 Jian-Feng Cai, et al. ∙

research

∙ 06/06/2023

Online Tensor Learning: Computational and Statistical Trade-offs, Adaptivity and Optimal Regret

We investigate a generalized framework for estimating latent low-rank te...

0 Jian-Feng Cai, et al. ∙

research

∙ 05/10/2023

Computationally Efficient and Statistically Optimal Robust High-Dimensional Linear Regression

High-dimensional linear regression under heavy-tailed noise or outlier c...

0 Yinan Shen, et al. ∙

research

∙ 03/14/2023

Asymptotically Sharp Upper Bound for the Column Subset Selection Problem

This paper investigates the spectral norm version of the column subset s...

0 Jian-Feng Cai, et al. ∙

research

∙ 10/26/2022

Provable Sample-Efficient Sparse Phase Retrieval Initialized by Truncated Power Method

We study the sparse phase retrieval problem, recovering an s-sparse leng...

0 Jian-Feng Cai, et al. ∙

research

∙ 08/09/2022

Two Stage Continuous Domain Regularization for Piecewise Constant Image Restoration

The finite-rate-of-innovation (FRI) framework which corresponds a signal...

0 Jian-Feng Cai, et al. ∙

research

∙ 07/15/2022

Approximation Theory of Total Variation Minimization for Data Completion

Total variation (TV) minimization is one of the most important technique...

0 Jian-Feng Cai, et al. ∙

research

∙ 04/20/2022

Nearly optimal bounds for the global geometric landscape of phase retrieval

The phase retrieval problem is concerned with recovering an unknown sign...

0 Jian-Feng Cai, et al. ∙

research

∙ 04/07/2022

Structured Gradient Descent for Fast Robust Low-Rank Hankel Matrix Completion

We study the robust matrix completion problem for the low-rank Hankel ma...

0 HanQin Cai, et al. ∙

research

∙ 03/02/2022

Computationally Efficient and Statistically Optimal Robust Low-rank Matrix and Tensor Estimation

Low-rank matrix estimation under heavy-tailed noise is challenging, both...

0 Yinan Shen, et al. ∙

research

∙ 12/15/2021

The global landscape of phase retrieval II: quotient intensity models

A fundamental problem in phase retrieval is to reconstruct an unknown si...

0 Jian-Feng Cai, et al. ∙

research

∙ 12/15/2021

The global landscape of phase retrieval I: perturbed amplitude models

A fundamental task in phase retrieval is to recover an unknown signal ∈ ...

0 Jian-Feng Cai, et al. ∙

research

∙ 12/15/2021

Sample-Efficient Sparse Phase Retrieval via Stochastic Alternating Minimization

In this work we propose a nonconvex two-stage stochastic alternating min...

0 Jian-Feng Cai, et al. ∙

research

∙ 12/03/2021

Fast Projected Newton-like Method for Precision Matrix Estimation with Nonnegative Partial Correlations

We study the problem of estimating precision matrices in multivariate Ga...

0 Jiaxi Ying, et al. ∙

research

∙ 08/27/2021

Provable Tensor-Train Format Tensor Completion by Riemannian Optimization

The tensor train (TT) format enjoys appealing advantages in handling str...

0 Jian-Feng Cai, et al. ∙

research

∙ 03/16/2021

Generalized Low-rank plus Sparse Tensor Estimation by Fast Riemannian Optimization

We investigate a generalized framework to estimate a latent low-rank plu...

0 Jian-Feng Cai, et al. ∙

research

∙ 12/12/2020

Image Restoration: Structured Low Rank Matrix Framework for Piecewise Smooth Functions and Beyond

Recently, mapping a signal/image into a low rank Hankel/Toeplitz matrix ...

0 Jian-Feng Cai, et al. ∙

research

∙ 07/17/2020

Provable Near-Optimal Low-Multilinear-Rank Tensor Recovery

We consider the problem of recovering a low-multilinear-rank tensor from...

0 Jian-Feng Cai, et al. ∙

research

∙ 05/18/2020

Sparse Signal Recovery From Phaseless Measurements via Hard Thresholding Pursuit

In this paper, we consider the sparse phase retrival problem, recovering...

0 Jian-Feng Cai, et al. ∙

research

∙ 11/08/2019

Off-the-Grid Compressed Sensing MRI Reconstruction via Data Driven Tight Frame Regularization

Recently, the finite-rate-of-innovation (FRI) based continuous domain re...

0 Jian-Feng Cai, et al. ∙

research

∙ 10/13/2019

Fast and Robust Spectrally Sparse Signal Recovery: A Provable Non-Convex Approach via Robust Low-Rank Hankel Matrix Reconstruction

Consider a spectrally sparse signal x that consists of r complex sinusoi...

1 HanQin Cai, et al. ∙

research

∙ 06/12/2019

Optimal low rank tensor recovery

We investigate the sample size requirement for exact recovery of a high ...

0 Jian-Feng Cai, et al. ∙

research

∙ 06/09/2019

Fast Cadzow's Algorithm and a Gradient Variant

The Cadzow's algorithm is a signal denoising and recovery method which w...

0 Haifeng Wang, et al. ∙

research

∙ 03/10/2019

Fast Single Image Reflection Suppression via Convex Optimization

Removing undesired reflections from images taken through the glass is of...

4 Yang Yang, et al. ∙

research

∙ 11/22/2018

Enhanced Expressive Power and Fast Training of Neural Networks by Random Projections

Random projections are able to perform dimension reduction efficiently f...

0 Jian-Feng Cai, et al. ∙

research

∙ 10/20/2018

Data-Driven Tight Frame for Cryo-EM Image Denoising and Conformational Classification

The cryo-electron microscope (cryo-EM) is increasingly popular these yea...

0 Yin Xian, et al. ∙

research

∙ 09/27/2018

Towards the optimal construction of a loss function without spurious local minima for solving quadratic equations

The problem of finding a vector x which obeys a set of quadratic equatio...

0 Zhenzhen Li, et al. ∙

research

∙ 09/11/2018

Exploiting the structure effectively and efficiently in low rank matrix recovery

Low rank model arises from a wide range of applications, including machi...

0 Jian-Feng Cai, et al. ∙

research

∙ 04/06/2016

Hankel Matrix Nuclear Norm Regularized Tensor Completion for N-dimensional Exponential Signals

Signals are generally modeled as a superposition of exponential function...

0 Jiaxi Ying, et al. ∙

research

∙ 09/15/2015

Precise Phase Transition of Total Variation Minimization

Characterizing the phase transitions of convex optimizations in recoveri...

0 Bingwen Zhang, et al. ∙

research

∙ 04/29/2015

Projected Iterative Soft-thresholding Algorithm for Tight Frames in Compressed Sensing Magnetic Resonance Imaging

Compressed sensing has shown great potentials in accelerating magnetic r...

0 Yunsong Liu, et al. ∙

research

∙ 03/10/2015

Fast Multi-class Dictionaries Learning with Geometrical Directions in MRI Reconstruction

Objective: Improve the reconstructed image with fast and multi-class dic...

0 Zhifang Zhan, et al. ∙

research

∙ 03/10/2015

Robust recovery of complex exponential signals from random Gaussian projections via low rank Hankel matrix reconstruction

This paper explores robust recovery of a superposition of R distinct com...

0 Jian-Feng Cai, et al. ∙

research

∙ 12/02/2013

Precise Semidefinite Programming Formulation of Atomic Norm Minimization for Recovering d-Dimensional (d≥ 2) Off-the-Grid Frequencies

Recent research in off-the-grid compressed sensing (CS) has demonstrated...

0 Weiyu Xu, et al. ∙

research

∙ 01/28/2013

Guarantees of Total Variation Minimization for Signal Recovery

In this paper, we consider using total variation minimization to recover...

0 Jian-Feng Cai, et al. ∙

research

∙ 12/05/2010

Split Bregman Method for Sparse Inverse Covariance Estimation with Matrix Iteration Acceleration

We consider the problem of estimating the inverse covariance matrix by m...

0 Gui-Bo Ye, et al. ∙

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