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5 papers
Randomized Kaczmarz for Tensor Linear Systems
Anna Ma, Denali Molitor
Solving linear systems of equations is a fundamental problem in mathematics. When the linear system is so large that it cannot be loaded into memory at once, iterative methods such…
Greed Works: An Improved Analysis of Sampling Kaczmarz-Motzkin
Jamie Haddock, Anna Ma
Stochastic iterative algorithms have gained recent interest in machine learning and signal processing for solving large-scale systems of equations, . One such example is the…
Stochastic Iterative Hard Thresholding for Low-Tucker-Rank Tensor Recovery
Rachel Grotheer, Shuang Li, Anna Ma +2
Low-rank tensor recovery problems have been widely studied in many applications of signal processing and machine learning. Tucker decomposition is known as one of the most popular…
Iterative Hard Thresholding for Low CP-rank Tensor Models
Rachel Grotheer, Shuang Li, Anna Ma +2
Recovery of low-rank matrices from a small number of linear measurements is now well-known to be possible under various model assumptions on the measurements. Such results demonstr…
Data-driven Algorithm Selection and Parameter Tuning: Two Case studies in Optimization and Signal Processing
Jesus A. De Loera, Jamie Haddock, Anna Ma +1
Machine learning algorithms typically rely on optimization subroutines and are well-known to provide very effective outcomes for many types of problems. Here, we flip the reliance…