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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...
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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,...
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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...
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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 ...
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06/17/2022
Riemannian CUR Decompositions for Robust Principal Component Analysis
Robust Principal Component Analysis (PCA) has received massive attention...
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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...
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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 ...
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08/23/2021
Fast Robust Tensor Principal Component Analysis via Fiber CUR Decomposition
We study the problem of tensor robust principal component analysis (TRPC...
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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...
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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...
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01/05/2021
Robust CUR Decomposition: Theory and Imaging Applications
This paper considers the use of Robust PCA in a CUR decomposition framew...
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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...
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10/06/2020
SCOBO: Sparsity-Aware Comparison Oracle Based Optimization
We study derivative-free optimization for convex functions where we furt...
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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...
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10/13/2019