5 citations · 22 across the 27 of their papers we have counts for
31 papers
Quantile-based Loss Filtering for Outlier-Robust Stochastic Gradient Descent
Jamie Haddock, Anna Ma, Elizaveta Rebrova
We study loss-based filtering for finite-sum optimization with a subset of corrupted component functions whose gradients may be highly unreliable. Motivated by minimum-loss-based S…
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…
Randomized Kaczmarz methods for t-product tensor linear systems with factorized operators
Alejandra Castillo, Jamie Haddock, Iryna Hartsock +7
Randomized iterative algorithms, such as the randomized Kaczmarz method, have gained considerable popularity due to their efficacy in solving matrix-vector and matrix-matrix regres…
The text2term tool to map free-text descriptions of biomedical terms to ontologies
Rafael S. Gonçalves, Jason Payne, Amelia Tan +3
There is an ongoing need for scalable tools to aid researchers in both retrospective and prospective standardization of discrete entity types -- such as disease names, cell types o…