A Sampling Kaczmarz-Motzkin Algorithm for Linear Feasibility. - Jesús A. De Loera; Jamie Haddock; Deanna Needell (SIAM J. Sci. Comput., 2017)

A Bayesian Approach for Asynchronous Parallel Sparse Recovery. - Alireza Zaeemzadeh; Jamie Haddock; Nazanin Rahnavard; Deanna Needell (ACSSC, 2018)

Randomized Projection Methods for Corrupted Linear Systems. - Jamie Haddock; Deanna Needell (CoRR, 2018)

Convergence of Iterative Hard Thresholding Variants with Application to Asynchronous Parallel Methods for Sparse Recovery. - Jamie Haddock; Deanna Needell; Alireza Zaeemzadeh; Nazanin Rahnavard (ACSSC, 2019)

Neural Nonnegative Matrix Factorization for Hierarchical Multilayer Topic Modeling. - Mengdi Gao; Jamie Haddock; Denali Molitor; Deanna Needell; Eli Sadovnik; Tyler Will; Runyu Zhang (CAMSAP, 2019)

Data-driven Algorithm Selection and Parameter Tuning: Two Case studies in Optimization and Signal Processing. - Jesús A. De Loera; Jamie Haddock; Anna Ma; Deanna Needell (CoRR, 2019)

Greed Works: An Improved Analysis of Sampling Kaczmarz-Motkzin. - Jamie Haddock; Anna Ma (CoRR, 2019)

Randomized Projection Methods for Linear Systems with Arbitrarily Large Sparse Corruptions. - Jamie Haddock; Deanna Needell (SIAM J. Sci. Comput., 2019)

Stochastic Gradient Descent Variants for Corrupted Systems of Linear Equations. - Jamie Haddock; Deanna Needell; Elizaveta Rebrova; William Swartworth (CISS, 2020)

On Nonnegative CP Tensor Decomposition Robustness to Noise. - Jamie Haddock; Lara Kassab; Alona Kryshchenko; Deanna Needell (ITA, 2020)

Feature Selection from Lyme Disease Patient Survey Using Machine Learning. - Joshua Vendrow; Jamie Haddock; Deanna Needell; Lorraine Johnson (Algorithms, 2020)

On Large-Scale Dynamic Topic Modeling with Nonnegative CP Tensor Decomposition. - Miju Ahn; Nicole Eikmeier; Jamie Haddock; Lara Kassab; Alona Kryshchenko; Kathryn Leonard; Deanna Needell; R. W. M. A. Madushani; Elena Sizikova; Chuntian Wang (CoRR, 2020)

Feature Selection on Lyme Disease Patient Survey Data. - Joshua Vendrow; Jamie Haddock; Deanna Needell; Lorraine Johnson (CoRR, 2020)

Semi-supervised NMF Models for Topic Modeling in Learning Tasks. - Jamie Haddock; Lara Kassab; Sixian Li; Alona Kryshchenko; Rachel Grotheer; Elena Sizikova; Chuntian Wang; Thomas Merkh; R. W. M. A. Madushani; Miju Ahn; Deanna Needell; Kathryn Leonard (CoRR, 2020)

On Application of Block Kaczmarz Methods in Matrix Factorization. - Edwin Chau; Jamie Haddock (CoRR, 2020)

The Minimum Euclidean-Norm Point in a Convex Polytope: Wolfe's Combinatorial Algorithm is Exponential. - Jesús A. De Loera; Jamie Haddock; Luis Rademacher (SIAM J. Comput., 2020)

Semi-supervised Nonnegative Matrix Factorization for Document Classification. - Jamie Haddock; Lara Kassab; Sixian Li; Alona Kryshchenko; Rachel Grotheer; Elena Sizikova; Chuntian Wang; Thomas Merkh; R. W. M. A. Madushani; Miju Ahn; Deanna Needell; Kathryn Leonard (ACSCC, 2021)

Neural Nonnegative CP Decomposition for Hierarchical Tensor Analysis. - Joshua Vendrow; Jamie Haddock; Deanna Needell (ACSCC, 2021)

On a Guided Nonnegative Matrix Factorization. - Joshua Vendrow; Jamie Haddock; Elizaveta Rebrova; Deanna Needell (ICASSP, 2021)

Data-driven algorithm selection and tuning in optimization and signal processing. - Jesús A. De Loera; Jamie Haddock; Anna Ma; Deanna Needell (Ann. Math. Artif. Intell., 2021)

Greed Works: An Improved Analysis of Sampling Kaczmarz-Motzkin. - Jamie Haddock; Anna Ma (SIAM J. Math. Data Sci., 2021)

A Generalized Hierarchical Nonnegative Tensor Decomposition. - Joshua Vendrow; Jamie Haddock; Deanna Needell (ICASSP, 2022)

Joint NMF for Identification of Shared Features in Datasets and a Dataset Distance Measure. - Hannah Friedman; Amani R. Maina-Kilaas; Julianna Schalkwyk; Hina Ahmed; Jamie Haddock (CoRR, 2022)

Automatic Infectious Disease Classification Analysis with Concept Discovery. - Elena Sizikova; Joshua Vendrow; Xu Cao; Rachel Grotheer; Jamie Haddock; Lara Kassab; Alona Kryshchenko; Thomas Merkh; R. W. M. A. Madushani; Kenny Moise; Annie Ulichney; Huy V. Vo; et al. (CoRR, 2022)

Quantile-Based Iterative Methods for Corrupted Systems of Linear Equations. - Jamie Haddock; Deanna Needell; Elizaveta Rebrova; William Swartworth (SIAM J. Matrix Anal. Appl., 2022)

Paving the Way for Consensus: Convergence of Block Gossip Algorithms. - Jamie Haddock; Benjamin Jarman; Chen Yap (IEEE Trans. Inf. Theory, 2022)

On Subsampled Quantile Randomized Kaczmarz. - Jamie Haddock; Anna Ma; Elizaveta Rebrova (Allerton, 2023)

An Interpretable Joint Nonnegative Matrix Factorization-Based Point Cloud Distance Measure. - Hannah Friedman; Amani R. Maina-Kilaas; Julianna Schalkwyk; Hina Ahmed; Jamie Haddock (CISS, 2023)

Neural Nonnegative Matrix Factorization for Hierarchical Multilayer Topic Modeling. - Tyler Will; Runyu Zhang; Eli Sadovnik; Mengdi Gao; Joshua Vendrow; Jamie Haddock; Denali Molitor; Deanna Needell (CoRR, 2023)

Nonbacktracking Spectral Clustering of Nonuniform Hypergraphs. - Philip S. Chodrow; Nicole Eikmeier; Jamie Haddock (SIAM J. Math. Data Sci., 2023)

On Quantile Randomized Kaczmarz for Linear Systems with Time-Varying Noise and Corruption. - Nestor Coria; Jamie Haddock; Jaime Pacheco 002 (CoRR, 2024)

Block Matrix and Tensor Randomized Kaczmarz Methods for Linear Feasibility Problems. - Minxin Zhang; Jamie Haddock; Deanna Needell (CoRR, 2024)

Randomized Kaczmarz methods for t-product tensor linear systems with factorized operators. - Alejandra Castillo; Jamie Haddock; Iryna Hartsock; Paulina Hoyos; Lara Kassab; Alona Kryshchenko; Kamila Larripa; Deanna Needell; Shambhavi Suryanarayanan; Karamatou Yacoubou Djima (CoRR, 2024)

Zero forcing with random sets. - Bryan Curtis; Luyining Gan; Jamie Haddock; Rachel Lawrence; Sam Spiro (Discret. Math., 2024)

The text2term tool to map free-text descriptions of biomedical terms to ontologies. - Rafael S. Gonçalves 001; Jason Payne; Amelia L. M. Tan; Carmen Benitez; Jamie Haddock; Robert Gentleman (Database J. Biol. Databases Curation, 2024)

Quantile-Based Randomized Kaczmarz for Corrupted Tensor Linear Systems. - Alejandra Castillo; Jamie Haddock; Iryna Hartsock; Paulina Hoyos; Lara Kassab; Alona Kryshchenko; Kamila Larripa; Deanna Needell; Shambhavi Suryanarayanan; Karamatou Yacoubou Djima (CoRR, 2025)

Block Gauss-Seidel methods for t-product tensor regression. - Alejandra Castillo; Jamie Haddock; Iryna Hartsock; Paulina Hoyos; Lara Kassab; Alona Kryshchenko; Kamila Larripa; Deanna Needell; Shambhavi Suryanarayanan; Karamatou Yacoubou Djima (CoRR, 2025)