research
∙
08/31/2023
A Note on Randomized Kaczmarz Algorithm for Solving Doubly-Noisy Linear Systems
Large-scale linear systems, Ax=b, frequently arise in practice and deman...
share
research
∙
08/15/2023
On Subsampled Quantile Randomized Kaczmarz
When solving noisy linear systems Ax = b + c, the theoretical and empiri...
research
∙
06/07/2023
Stochastic Natural Thresholding Algorithms
Sparse signal recovery is one of the most fundamental problems in variou...
research
∙
06/01/2023
Efficient and Robust Bayesian Selection of Hyperparameters in Dimension Reduction for Visualization
We introduce an efficient and robust auto-tuning framework for hyperpara...
research
∙
06/02/2022
Robust recovery of low-rank matrices and low-tubal-rank tensors from noisy sketches
A common approach for compressing large-scale data is through matrix ske...
research
∙
05/31/2022
AVIDA: Alternating method for Visualizing and Integrating Data
High-dimensional multimodal data arises in many scientific fields. The i...
research
∙
08/30/2021
On the Number of Faces and Radii of Cells Induced by Gaussian Spherical Tessellations
We study a geometric property related to spherical hyperplane tessellati...
research
∙
06/01/2020
Randomized Kaczmarz for Tensor Linear Systems
Solving linear systems of equations is a fundamental problem in mathemat...
research
∙
12/07/2019
Greed Works: An Improved Analysis of Sampling Kaczmarz-Motkzin
Stochastic iterative algorithms have gained recent interest in machine l...
research
∙
09/23/2019
Stochastic Iterative Hard Thresholding for Low-Tucker-Rank Tensor Recovery
Low-rank tensor recovery problems have been widely studied in many appli...
research
∙
08/22/2019
Iterative Hard Thresholding for Low CP-rank Tensor Models
Recovery of low-rank matrices from a small number of linear measurements...
research
∙
05/31/2019
Data-driven Algorithm Selection and Parameter Tuning: Two Case studies in Optimization and Signal Processing
Machine learning algorithms typically rely on optimization subroutines a...
research
∙
07/12/2018
An Approximate Message Passing Framework for Side Information
Approximate message passing (AMP) methods have gained recent traction in...
research
∙
05/31/2018
Analysis of Fast Structured Dictionary Learning
Sparsity-based models and techniques have been exploited in many signal ...
research
∙
02/01/2018
Analysis of Fast Alternating Minimization for Structured Dictionary Learning
Methods exploiting sparsity have been popular in imaging and signal proc...
research
∙
01/31/2018
Compressed Anomaly Detection with Multiple Mixed Observations
We consider a collection of independent random variables that are identi...
research
∙
11/07/2017
Sparse Randomized Kaczmarz for Support Recovery of Jointly Sparse Corrupted Multiple Measurement Vectors
While single measurement vector (SMV) models have been widely studied in...
research
∙
11/05/2017
Stochastic Greedy Algorithms For Multiple Measurement Vectors
Sparse representation of a single measurement vector (SMV) has been expl...
research
∙
05/08/2014
