Testing Hereditary Properties of Sequences. - Cody R. Freitag; Eric Price 001; William J. Swartworth (APPROX-RANDOM, 2017)

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

An Untrained One-layer Convolutional Network-based Method for Line Spectral Estimation. - Shuang Li 003; Deanna Needell; William Swartworth (ACSCC, 2021)

Reconstructing Piezoelectric Responses over a Lattice: Adaptive Sampling of Low Dimensional Time Series Representations Based on Relative Isolation and Gradient Size. - Michael R. Lindstrom; William J. Swartworth; Deanna Needell (SMC, 2021)

Population-Based Hierarchical Non-Negative Matrix Factorization for Survey Data. - Xiaofu Ding; Xinyu Dong; Olivia McGough; Chenxin Shen; Annie Ulichney; Ruiyao Xu; William Swartworth; Jocelyn T. Chi; Deanna Needell (BDCAT, 2022)

Testing Positive Semidefiniteness Using Linear Measurements. - Deanna Needell; William Swartworth; David P. Woodruff (FOCS, 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)

SP2 : A Second Order Stochastic Polyak Method. - Shuang Li 003; William J. Swartworth; Martin Takác 001; Deanna Needell; Robert M. Gower (ICLR, 2023)

Training shallow ReLU networks on noisy data using hinge loss: when do we overfit and is it benign? - Erin George; Michael Murray; William Swartworth; Deanna Needell (NeurIPS, 2023)

Nearly Optimal Bounds for Cyclic Forgetting. - William Swartworth; Deanna Needell; Rachel A. Ward; Mark Kong; Halyun Jeong (NeurIPS, 2023)

Optimal Eigenvalue Approximation via Sketching. - William Swartworth; David P. Woodruff (STOC, 2023)

Fast and Low-Memory Compressive Sensing Algorithms for Low Tucker-Rank Tensor Approximation from Streamed Measurements. - Cullen Haselby; Mark A. Iwen; Deanna Needell; Elizaveta Rebrova; William Swartworth (CoRR, 2023)

Selectable Set Randomized Kaczmarz. - Yotam Yaniv; Jacob D. Moorman; William Swartworth; Thomas K. Tu; Daji Landis; Deanna Needell (Numer. Linear Algebra Appl., 2023)

Fast Sampling-Based Sketches for Tensors. - William J. Swartworth; David P. Woodruff (ICML, 2024)

Improving the Bit Complexity of Communication for Distributed Convex Optimization. - Mehrdad Ghadiri; Yin Tat Lee; Swati Padmanabhan; William Swartworth; David P. Woodruff; Guanghao Ye (STOC, 2024)

Tight Bounds for Heavy-Hitters and Moment Estimation in the Sliding Window Model. - Shiyuan Feng; William Swartworth; David P. Woodruff (ICALP, 2025)

Tight Sampling Bounds for Eigenvalue Approximation. - William Swartworth; David P. Woodruff (SODA, 2025)

Understanding the Kronecker Matrix-Vector Complexity of Linear Algebra. - Raphael A. Meyer; William Swartworth; David P. Woodruff (CoRR, 2025)

Unbiased Insights: Optimal Streaming Algorithms for ℓp Sampling, the Forget Model, and Beyond. - Honghao Lin; Hoai-An Nguyen; William Swartworth; David P. Woodruff (CoRR, 2025)