HanQin Cai | DeepAI

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∙ 05/29/2023

Towards Constituting Mathematical Structures for Learning to Optimize

Learning to Optimize (L2O), a technique that utilizes machine learning t...

0 Jialin Liu, et al. ∙

∙ 05/06/2023

Robust Tensor CUR Decompositions: Rapid Low-Tucker-Rank Tensor Recovery with Sparse Corruption

We study the tensor robust principal component analysis (TRPCA) problem,...

0 HanQin Cai, et al. ∙

∙ 03/17/2023

Non-convex approaches for low-rank tensor completion under tubal sampling

Tensor completion is an important problem in modern data analysis. In th...

0 Zheng Tan, et al. ∙

∙ 08/20/2022

Matrix Completion with Cross-Concentrated Sampling: Bridging Uniform Sampling and CUR Sampling

While uniform sampling has been widely studied in the matrix completion ...

8 HanQin Cai, et al. ∙

∙ 06/17/2022

Riemannian CUR Decompositions for Robust Principal Component Analysis

Robust Principal Component Analysis (PCA) has received massive attention...

0 Keaton Hamm, et al. ∙

∙ 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. ∙

∙ 10/11/2021

Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection

Robust principal component analysis (RPCA) is a critical tool in modern ...

15 HanQin Cai, et al. ∙

∙ 08/23/2021

Fast Robust Tensor Principal Component Analysis via Fiber CUR Decomposition

We study the problem of tensor robust principal component analysis (TRPC...

4 HanQin Cai, et al. ∙

∙ 03/19/2021

Mode-wise Tensor Decompositions: Multi-dimensional Generalizations of CUR Decompositions

Low rank tensor approximation is a fundamental tool in modern machine le...

5 HanQin Cai, et al. ∙

∙ 02/21/2021

A Zeroth-Order Block Coordinate Descent Algorithm for Huge-Scale Black-Box Optimization

We consider the zeroth-order optimization problem in the huge-scale sett...

5 HanQin Cai, et al. ∙

∙ 01/05/2021

Robust CUR Decomposition: Theory and Imaging Applications

This paper considers the use of Robust PCA in a CUR decomposition framew...

1 HanQin Cai, et al. ∙

∙ 10/14/2020

Rapid Robust Principal Component Analysis: CUR Accelerated Inexact Low Rank Estimation

Robust principal component analysis (RPCA) is a widely used tool for dim...

1 HanQin Cai, et al. ∙

∙ 10/06/2020

SCOBO: Sparsity-Aware Comparison Oracle Based Optimization

We study derivative-free optimization for convex functions where we furt...

6 HanQin Cai, et al. ∙

∙ 03/29/2020

Zeroth-Order Regularized Optimization (ZORO): Approximately Sparse Gradients and Adaptive Sampling

We consider the problem of minimizing a high-dimensional objective funct...

1 HanQin Cai, et al. ∙

∙ 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. ∙

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