3 citations · 5 across the 13 of their papers we have counts for
3 papers · 1 filter
Beyond Expectation: Concentration Inequalities for Randomized Iterative Methods
Toby Anderson, Max Collins, Jamie Haddock +2
Stochastic iterative methods are useful in a variety of large-scale numerical linear algebraic, machine learning, and statistical problems, in part due to their low-memory footprin…
Block Gauss-Seidel methods for t-product tensor regression
Alejandra Castillo, Jamie Haddock, Iryna Hartsock +7
Randomized iterative algorithms, such as the randomized Kaczmarz method and the randomized Gauss-Seidel method, have gained considerable popularity due to their efficacy in solving…
Quantile-Based Randomized Kaczmarz for Corrupted Tensor Linear Systems
Alejandra Castillo, Jamie Haddock, Iryna Hartsock +7
The reconstruction of tensor-valued signals from corrupted measurements, known as tensor regression, has become essential in many multi-modal applications such as hyperspectral ima…