Software Requirements Specification of a University Class Scheduler. - Deanna Needell; Jeff A. Stuart; Tamara C. Thiel; Sergiu Dascalu; Frederick C. Harris Jr. (Software Engineering Research and Practice, 2003)

Greedy signal recovery review. - Deanna Needell; Joel A. Tropp; Roman Vershynin (ACSCC, 2008)

Greedy signal recovery and uncertainty principles. - Deanna Needell; Roman Vershynin (Computational Imaging, 2008)

Noisy Signal Recovery via Iterative Reweighted L1-Minimization - Deanna Needell (CoRR, 2009)

Topics in Compressed Sensing - Deanna Needell (CoRR, 2009)

Uniform Uncertainty Principle and Signal Recovery via Regularized Orthogonal Matching Pursuit. - Deanna Needell; Roman Vershynin (Found. Comput. Math., 2009)

Mixed operators in compressed sensing. - Matthew A. Herman; Deanna Needell (CISS, 2010)

CoSaMP: iterative signal recovery from incomplete and inaccurate samples. - Deanna Needell; Joel A. Tropp (Commun. ACM, 2010)

Compressed Sensing with Coherent and Redundant Dictionaries - Emmanuel J. Candès; Yonina C. Eldar; Deanna Needell (CoRR, 2010)

Signal Recovery From Incomplete and Inaccurate Measurements Via Regularized Orthogonal Matching Pursuit. - Deanna Needell; Roman Vershynin (IEEE J. Sel. Top. Signal Process., 2010)

Unicity conditions for low-rank matrix recovery - Yonina C. Eldar; Deanna Needell; Yaniv Plan (CoRR, 2011)

Acceleration of randomized Kaczmarz method via the Johnson-Lindenstrauss Lemma. - Yonina C. Eldar; Deanna Needell (Numer. Algorithms, 2011)

CoSaMP with redundant dictionaries. - Mark A. Davenport; Deanna Needell; Michael B. Wakin (ACSCC, 2012)

Paved with Good Intentions: Analysis of a Randomized Block Kaczmarz Method - Deanna Needell; Joel A. Tropp (CoRR, 2012)

Total variation minimization for stable multidimensional signal recovery - Deanna Needell; Rachel A. Ward (CoRR, 2012)

Spectral Clustering: An empirical study of Approximation Algorithms and its Application to the Attrition Problem - B. Cung; T. Jin; Juan Ramirez; A. Thompson; Christos Boutsidis; Deanna Needell (CoRR, 2012)

Two-part reconstruction in compressed sensing. - Yanting Ma; Dror Baron; Deanna Needell (GlobalSIP, 2013)

Kaczmarz Algorithm with Soft Constraints for User Interface Layout. - Noreen Jamil; Deanna Needell; Johannes Müller 005; Christof Lutteroth; Gerald Weber (ICTAI, 2013)

Guaranteed sparse signal recovery with highly coherent sensing matrices. - Guangliang Chen; Atul Divekar; Deanna Needell (CoRR, 2013)

Greedy Signal Space Methods for incoherence and beyond. - Raja Giryes; Deanna Needell (CoRR, 2013)

On the Mathematics of Music: From Chords to Fourier Analysis. - Nathan Lenssen; Deanna Needell (CoRR, 2013)

Stochastic gradient descent and the randomized Kaczmarz algorithm. - Deanna Needell; Nathan Srebro; Rachel A. Ward (CoRR, 2013)

Using Correlated Subset Structure for Compressive Sensing Recovery - Atul Divekar; Deanna Needell (CoRR, 2013)

Super-resolution via superset selection and pruning - Laurent Demanet; Deanna Needell; Nam Nguyen (CoRR, 2013)

Stable Image Reconstruction Using Total Variation Minimization. - Deanna Needell; Rachel A. Ward (SIAM J. Imaging Sci., 2013)

Near-Optimal Compressed Sensing Guarantees for Total Variation Minimization. - Deanna Needell; Rachel A. Ward (IEEE Trans. Image Process., 2013)

Signal Space CoSaMP for Sparse Recovery With Redundant Dictionaries. - Mark A. Davenport; Deanna Needell; Michael B. Wakin (IEEE Trans. Inf. Theory, 2013)

Improving image clustering using sparse text and the wisdom of the crowds. - Anna Ma; Arjuna Flenner; Deanna Needell; Allon G. Percus (ACSSC, 2014)

A comparison of clustering and missing data methods for health sciences. - Ran Zhao 004; Deanna Needell; Christopher Johansen; Jerry L. Grenard (ACSSC, 2014)

Practical approximate projection schemes in greedy signal space methods. - Chris Garnatz; Xiaoyi Gu; Alison Kingman; James LaManna; Deanna Needell; Shenyinying Tu (CoRR, 2014)

Near Oracle Performance of Signal Space Greedy Methods. - Raja Giryes; Deanna Needell (CoRR, 2014)

Two-Part Reconstruction With Noisy-Sudocodes. - Yanting Ma; Dror Baron; Deanna Needell (IEEE Trans. Signal Process., 2014)

One-bit Compressive Sensing with partial support. - Phillip North; Deanna Needell (CAMSAP, 2015)

A note on practical approximate projection schemes in signal space methods. - Xiaoyi Gu; Deanna Needell; Shenyinying Tu (CoRR, 2015)

Near oracle performance and block analysis of signal space greedy methods. - Raja Giryes; Deanna Needell (J. Approx. Theory, 2015)

Block Kaczmarz Method with Inequalities. - Jonathan Briskman; Deanna Needell (J. Math. Imaging Vis., 2015)

Compressive Sensing with Redundant Dictionaries and Structured Measurements. - Felix Krahmer; Deanna Needell; Rachel A. Ward (SIAM J. Math. Anal., 2015)

Convergence Properties of the Randomized Extended Gauss-Seidel and Kaczmarz Methods. - Anna Ma; Deanna Needell; Aaditya Ramdas (SIAM J. Matrix Anal. Appl., 2015)

Methods for quantized compressed sensing. - Hao-Jun Michael Shi; Mindy Case; Xiaoyi Gu; Shenyinying Tu; Deanna Needell (ITA, 2016)

One-Bit Compressive Sensing of Dictionary-Sparse Signals. - Richard G. Baraniuk; Simon Foucart; Deanna Needell; Yaniv Plan; Mary Wootters (CoRR, 2016)

Tolerant Compressed Sensing With Partially Coherent Sensing Matrices. - Tobias Birnbaum; Yonina C. Eldar; Deanna Needell (CoRR, 2016)

A Practical Study of Longitudinal Reference Based Compressed Sensing for MRI. - Samuel Birns; Bohyun Kim; Stephanie Ku; Kevin Stangl; Deanna Needell (CoRR, 2016)

Weighted ℓ1-Minimization for Sparse Recovery under Arbitrary Prior Information. - Deanna Needell; Rayan Saab; Tina Woolf (CoRR, 2016)

Batched Stochastic Gradient Descent with Weighted Sampling. - Deanna Needell; Rachel A. Ward (CoRR, 2016)

Stochastic gradient descent, weighted sampling, and the randomized Kaczmarz algorithm. - Deanna Needell; Nathan Srebro; Rachel A. Ward (Math. Program., 2016)

Constrained Adaptive Sensing. - Mark A. Davenport; Andrew K. Massimino; Deanna Needell; Tina Woolf (IEEE Trans. Signal Process., 2016)

Simple Object Classification Using Binary Data. - Deanna Needell; Rayan Saab; Tina Woolf (AAAI Fall Symposia, 2017)

Conditional approximate message passing with side information. - Dror Baron; Anna Ma; Deanna Needell; Cynthia Rush; Tina Woolf (ACSSC, 2017)

An asynchronous parallel approach to sparse recovery. - Deanna Needell; Tina Woolf (ITA, 2017)

Stochastic Greedy Algorithms For Multiple Measurement Vectors. - Jing Qin 003; Shuang Li 003; Deanna Needell; Anna Ma; Rachel Grotheer; Chenxi Huang 006; Natalie Durgin (CoRR, 2017)

Sparse Randomized Kaczmarz for Support Recovery of Jointly Sparse Corrupted Multiple Measurement Vectors. - Natalie Durgin; Rachel Grotheer; Chenxi Huang 006; Shuang Li 003; Anna Ma; Deanna Needell; Jing Qin 003 (CoRR, 2017)

Rows versus Columns: Randomized Kaczmarz or Gauss-Seidel for Ridge Regression. - Ahmed Hefny; Deanna Needell; Aaditya Ramdas (SIAM J. Sci. Comput., 2017)

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

Exponential Decay of Reconstruction Error From Binary Measurements of Sparse Signals. - Richard G. Baraniuk; Simon Foucart; Deanna Needell; Yaniv Plan; Mary Wootters (IEEE Trans. Inf. Theory, 2017)

Linear Convergence of Stochastic Iterative Greedy Algorithms With Sparse Constraints. - Nam Nguyen; Deanna Needell; Tina Woolf (IEEE Trans. Inf. Theory, 2017)

A Gradient Descent Approach for Incomplete Linear Systems. - Anna Ma; Deanna Needell (ACSSC, 2018)

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

Matrix Completion for Structured Observations. - Denali Molitor; Deanna Needell (ITA, 2018)

Analysis of Fast Alternating Minimization for Structured Dictionary Learning. - Saiprasad Ravishankar; Anna Ma; Deanna Needell (ITA, 2018)

Compressed Anomaly Detection with Multiple Mixed Observations. - Natalie Durgin; Rachel Grotheer; Chenxi Huang 006; Shuang Li 003; Anna Ma; Deanna Needell; Jing Qin 003 (CoRR, 2018)

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

Analysis of Fast Structured Dictionary Learning. - Saiprasad Ravishankar; Anna Ma; Deanna Needell (CoRR, 2018)

An iterative method for classification of binary data. - Denali Molitor; Deanna Needell (CoRR, 2018)

Simple Classification Using Binary Data. - Deanna Needell; Rayan Saab; Tina Woolf (J. Mach. Learn. Res., 2018)

Iterative Methods for Solving Factorized Linear Systems. - Anna Ma; Deanna Needell; Aaditya Ramdas (SIAM J. Matrix Anal. Appl., 2018)

Optimizing Quantization for Lasso Recovery. - Xiaoyi Gu; Shenyinying Tu; Hao-Jun Michael Shi; Mindy Case; Deanna Needell; Yaniv Plan (IEEE Signal Process. Lett., 2018)

Jointly Sparse Signal Recovery with Prior Info. - Natalie Durgin; Rachel Grotheer; Chenxi Huang 006; Shuang Li 003; Anna Ma; Deanna Needell; Jing Qin 003 (ACSSC, 2019)

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)

Sketching for Motzkin's Iterative Method for Linear Systems. - Elizaveta Rebrova; Deanna Needell (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)

Learning to Predict Human Stress Level with Incomplete Sensor Data from Wearable Devices. - Jyun-Yu Jiang; Zehan Chao; Andrea L. Bertozzi; Wei Wang 010; Sean D. Young; Deanna Needell (CIKM, 2019)

Fast Hyperspectral Diffuse Optical Imaging Method with Joint Sparsity. - Natalie Durgin; Rachel Grotheer; Chenxi Huang 006; Shuang Li 003; Anna Ma; Deanna Needell; Jing Qin 003 (EMBC, 2019)

Hierarchical Classification Using Binary Data. - Denali Molitor; Deanna Needell (AI Mag., 2019)

An algebraic perspective on integer sparse recovery. - Lenny Fukshansky; Deanna Needell; Benny Sudakov (Appl. Math. Comput., 2019)

Lattices From Tight Frames and Vertex Transitive Graphs. - Lenny Fukshansky; Deanna Needell; Josiah Park; Yuxin Xin (Electron. J. Comb., 2019)

Matrix Completion With Selective Sampling. - Christian Parkinson; Kevin Huynh; Deanna Needell (CoRR, 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)

Bias of Homotopic Gradient Descent for the Hinge Loss. - Denali Molitor; Deanna Needell; Rachel A. Ward (CoRR, 2019)

Iterative Hard Thresholding for Low CP-rank Tensor Models. - Rachel Grotheer; Shuang Li 003; Anna Ma; Deanna Needell; Jing Qin 003 (CoRR, 2019)

Adaptive Sketch-and-Project Methods for Solving Linear Systems. - Robert M. Gower; Denali Molitor; Jacob D. Moorman; Deanna Needell (CoRR, 2019)

Online matrix factorization for Markovian data and applications to Network Dictionary Learning. - Hanbaek Lyu; Deanna Needell; Laura Balzano (CoRR, 2019)

Topic-aware chatbot using Recurrent Neural Networks and Nonnegative Matrix Factorization. - Yuchen Guo; Nicholas Hanoian; Zhexiao Lin; Nicholas Liskij; Hanbaek Lyu; Deanna Needell; Jiahao Qu; Henry Sojico; Yuliang Wang; Zhe Xiong; Zhenhong Zou (CoRR, 2019)

Modified fuzzy clustering with segregated cluster centroids. - Tong Wu 006; Yicang Zhou; Yanni Xiao; Deanna Needell; Feiping Nie 001 (Neurocomputing, 2019)

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

An Approximate Message Passing Framework for Side Information. - Anna Ma; You Joe Zhou; Cynthia Rush; Dror Baron; Deanna Needell (IEEE Trans. Signal Process., 2019)

An Adaptation for Iterative Structured Matrix Completion. - Lara Kassab; Henry Adams; Deanna Needell (ACSSC, 2020)

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

COVID-19 Literature Topic-Based Search via Hierarchical NMF. - Rachel Grotheer; Longxiu Huang; Yihuan Huang; Alona Kryshchenko; Oleksandr Kryshchenko; Pengyu Li; Xia Li; Elizaveta Rebrova; Kyung Ha; Deanna Needell (NLP4COVID@EMNLP, 2020)

Clustering of Nonnegative Data and an Application to Matrix Completion. - Christopher Strohmeier; Deanna Needell (ICASSP, 2020)

Tensor Completion through Total Variation with Initialization from Weighted HOSVD. - Zehan Chao; Longxiu Huang; Deanna Needell (ITA, 2020)

Stochastic Iterative Hard Thresholding for Low-Tucker-Rank Tensor Recovery. - Rachel Grotheer; Shuang Li 003; Anna Ma; Deanna Needell; Jing Qin 003 (ITA, 2020)

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

Applications of Online Nonnegative Matrix Factorization to Image and Time-Series Data. - Hanbaek Lyu; Georg Menz; Deanna Needell; Christopher Strohmeier (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)

An Iterative Method for Structured Matrix Completion. - Henry Adams; Lara Kassab; Deanna Needell (CoRR, 2020)

Randomized Kaczmarz with Averaging. - Jacob D. Moorman; Thomas K. Tu; Denali Molitor; Deanna Needell (CoRR, 2020)

HOSVD-Based Algorithm for Weighted Tensor Completion. - Longxiu Huang; Deanna Needell (CoRR, 2020)

Tensor Completion through Total Variationwith Initialization from Weighted HOSVD. - Zehan Chao; Longxiu Huang; Deanna Needell (CoRR, 2020)

COVID-19 Time-series Prediction by Joint Dictionary Learning and Online NMF. - Hanbaek Lyu; Christopher Strohmeier; Georg Menz; Deanna Needell (CoRR, 2020)

Random Vector Functional Link Networks for Function Approximation on Manifolds. - Deanna Needell; Aaron A. Nelson; Rayan Saab; Palina Salanevich (CoRR, 2020)

Online nonnegative tensor factorization and CP-dictionary learning for Markovian data. - Christopher Strohmeier; Hanbaek Lyu; Deanna Needell (CoRR, 2020)

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

On Nonnegative Matrix and Tensor Decompositions for COVID-19 Twitter Dynamics. - Lara Kassab; Alona Kryshchenko; Hanbaek Lyu; Denali Molitor; Deanna Needell; Elizaveta Rebrova (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)

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)

QuantileRK: Solving Large-Scale Linear Systems with Corrupted, Noisy Data. - Benjamin Jarman; Deanna Needell (ACSCC, 2021)

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

Fast Robust Tensor Principal Component Analysis via Fiber CUR Decomposition *. - HanQin Cai; Zehan Chao; Longxiu Huang; Deanna Needell (ICCVW, 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)

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)

Analysis of Legal Documents via Non-negative Matrix Factorization Methods. - Ryan Budahazy; Lu Cheng 005; Yihuan Huang; Andrew Johnson; Pengyu Li; Joshua Vendrow; Zhoutong Wu; Denali Molitor; Elizaveta Rebrova; Deanna Needell (CoRR, 2021)

Analysis of Spatiotemporal Anomalies Using Persistent Homology: Case Studies with COVID-19 Data. - Abigail Hickok; Deanna Needell; Mason A. Porter (CoRR, 2021)

Fast Robust Tensor Principal Component Analysis via Fiber CUR Decomposition. - HanQin Cai; Zehan Chao; Longxiu Huang; Deanna Needell (CoRR, 2021)

Modewise Operators, the Tensor Restricted Isometry Property, and Low-Rank Tensor Recovery. - Mark A. Iwen; Deanna Needell; Michael Perlmutter; Elizaveta Rebrova (CoRR, 2021)

Robust recovery of bandlimited graph signals via randomized dynamical sampling. - Longxiu Huang; Deanna Needell; Sui Tang (CoRR, 2021)

HOSVD-Based Algorithm for Weighted Tensor Completion. - Zehan Chao; Longxiu Huang; Deanna Needell (J. Imaging, 2021)

Mode-wise Tensor Decompositions: Multi-dimensional Generalizations of CUR Decompositions. - HanQin Cai; Keaton Hamm; Longxiu Huang; Deanna Needell (J. Mach. Learn. Res., 2021)

On block Gaussian sketching for the Kaczmarz method. - Elizaveta Rebrova; Deanna Needell (Numer. Algorithms, 2021)

Robust CUR Decomposition: Theory and Imaging Applications. - HanQin Cai; Keaton Hamm; Longxiu Huang; Deanna Needell (SIAM J. Imaging Sci., 2021)

On Adaptive Sketch-and-Project for Solving Linear Systems. - Robert M. Gower; Denali Molitor; Jacob D. Moorman; Deanna Needell (SIAM J. Matrix Anal. Appl., 2021)

Lower Memory Oblivious (Tensor) Subspace Embeddings with Fewer Random Bits: Modewise Methods for Least Squares. - Mark A. Iwen; Deanna Needell; Elizaveta Rebrova; Ali Zare (SIAM J. Matrix Anal. Appl., 2021)

Weighted Matrix Completion From Non-Random, Non-Uniform Sampling Patterns. - Simon Foucart; Deanna Needell; Reese Pathak; Yaniv Plan; Mary Wootters (IEEE Trans. Inf. Theory, 2021)

Multi-Randomized Kaczmarz for Latent Class Regression. - Erin George; Yotam Yaniv; Deanna Needell (IEEECONF, 2022)

Online Signal Recovery via Heavy Ball Kaczmarz. - Benjamin Jarman; Yotam Yaniv; Deanna Needell (IEEECONF, 2022)

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)

On Audio Enhancement via Online Non-Negative Matrix Factorization. - Andrew Sack; Wenzhao Jiang; Michael Perlmutter; Palina Salanevich; Deanna Needell (CISS, 2022)

Testing Positive Semidefiniteness Using Linear Measurements. - Deanna Needell; William Swartworth; David P. Woodruff (FOCS, 2022)

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

The Manifold Scattering Transform for High-Dimensional Point Cloud Data. - Joyce A. Chew; Holly R. Steach; Siddharth Viswanath; Hau-Tieng Wu; Matthew J. Hirn; Deanna Needell; Matthew D. Vesely; Smita Krishnaswamy; Michael Perlmutter (TAG-ML, 2022)

Guided Semi-Supervised Non-Negative Matrix Factorization. - Pengyu Li; Christine Tseng; Yaxuan Zheng; Joyce A. Chew; Longxiu Huang; Benjamin Jarman; Deanna Needell (Algorithms, 2022)

Guided Semi-Supervised Non-negative Matrix Factorization on Legal Documents. - Pengyu Li; Christine Tseng; Yaxuan Zheng; Joyce A. Chew; Longxiu Huang; Benjamin Jarman; Deanna Needell (CoRR, 2022)

The Manifold Scattering Transform for High-Dimensional Point Cloud Data. - Joyce A. Chew; Holly R. Steach; Siddharth Viswanath; Hau-Tieng Wu; Matthew J. Hirn; Deanna Needell; Smita Krishnaswamy; Michael Perlmutter (CoRR, 2022)

On Block Accelerations of Quantile Randomized Kaczmarz for Corrupted Systems of Linear Equations. - Lu Cheng 005; Benjamin Jarman; Deanna Needell; Elizaveta Rebrova (CoRR, 2022)

Geometric Scattering on Measure Spaces. - Joyce A. Chew; Matthew J. Hirn; Smita Krishnaswamy; Deanna Needell; Michael Perlmutter; Holly R. Steach; Siddharth Viswanath; Hau-Tieng Wu (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)

Inference of Media Bias and Content Quality Using Natural-Language Processing. - Zehan Chao; Denali Molitor; Deanna Needell; Mason A. Porter (CoRR, 2022)

A Convergence Rate for Manifold Neural Networks. - Joyce A. Chew; Deanna Needell; Michael Perlmutter (CoRR, 2022)

Online Nonnegative CP-dictionary Learning for Markovian Data. - Hanbaek Lyu; Christopher Strohmeier; Deanna Needell (J. Mach. Learn. Res., 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)

Analysis of Spatial and Spatiotemporal Anomalies Using Persistent Homology: Case Studies with COVID-19 Data. - Abigail Hickok; Deanna Needell; Mason A. Porter (SIAM J. Math. Data Sci., 2022)

Stratified-NMF for Heterogeneous Data. - James Chapman 007; Yotam Yaniv; Deanna Needell (ACSSC, 2023)

Stochastic Natural Thresholding Algorithms. - Rachel Grotheer; Shuang Li 003; Anna Ma; Deanna Needell; Jing Qin 003 (ACSSC, 2023)

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

One-Bit Quadratic Compressed Sensing: From Sample Abundance to Linear Feasibility. - Arian Eamaz; Farhang Yeganegi; Deanna Needell; Mojtaba Soltanalian (ISIT, 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)

Distributed Randomized Kaczmarz for the Adversarial Workers. - Longxiu Huang; Xia Li; Deanna Needell (CoRR, 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)

Robust Tensor CUR Decompositions: Rapid Low-Tucker-Rank Tensor Recovery with Sparse Corruption. - HanQin Cai; Zehan Chao; Longxiu Huang; Deanna Needell (CoRR, 2023)

Detecting and Mitigating Indirect Stereotypes in Word Embeddings. - Erin George; Joyce A. Chew; Deanna Needell (CoRR, 2023)

Curvature corrected tangent space-based approximation of manifold-valued data. - Willem Diepeveen; Joyce A. Chew; Deanna Needell (CoRR, 2023)

Manifold Filter-Combine Networks. - Joyce A. Chew; Edward De Brouwer; Smita Krishnaswamy; Deanna Needell; Michael Perlmutter (CoRR, 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)

Continuous Semi-Supervised Nonnegative Matrix Factorization. - Michael R. Lindstrom; Xiaofu Ding; Feng Liu; Anand Somayajula; Deanna Needell (Algorithms, 2023)

Matrix Completion With Cross-Concentrated Sampling: Bridging Uniform Sampling and CUR Sampling. - HanQin Cai; Longxiu Huang; Pengyu Li; Deanna Needell (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Stratified Non-Negative Tensor Factorization. - Alexander Sietsema; Zerrin Vural; James Chapman 007; Yotam Yaniv; Deanna Needell (IEEECONF, 2024)

Convergence and Complexity Guarantee for Inexact First-order Riemannian Optimization Algorithms. - Yuchen Li; Laura Balzano; Deanna Needell; Hanbaek Lyu (ICML, 2024)

Benign overfitting in leaky ReLU networks with moderate input dimension. - Kedar Karhadkar; Erin George; Michael Murray; Guido F. Montúfar; Deanna Needell (NeurIPS, 2024)

Stochastic gradient descent for streaming linear and rectified linear systems with Massart noise. - Halyun Jeong; Deanna Needell; Elizaveta Rebrova (CoRR, 2024)

Kernel Alignment for Unsupervised Feature Selection via Matrix Factorization. - Ziyuan Lin; Deanna Needell (CoRR, 2024)

Fine-grained Analysis and Faster Algorithms for Iteratively Solving Linear Systems. - Michal Derezinski; Daniel LeJeune; Deanna Needell; Elizaveta Rebrova (CoRR, 2024)

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

Convergence of Manifold Filter-Combine Networks. - David R. Johnson; Joyce A. Chew; Siddharth Viswanath; Edward De Brouwer; Deanna Needell; Smita Krishnaswamy; Michael Perlmutter (CoRR, 2024)

Towards a Fairer Non-negative Matrix Factorization. - Lara Kassab; Erin George; Deanna Needell; Haowen Geng; Nika Jafar Nia; Aoxi Li (CoRR, 2024)

Differentially Private Random Feature Model. - Chunyang Liao; Deanna Needell; Alexander Xue (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)

Sparseness-constrained nonnegative tensor factorization for detecting topics at different time scales. - Lara Kassab; Alona Kryshchenko; Hanbaek Lyu; Denali Molitor; Deanna Needell; Elizaveta Rebrova; Jiahong Yuan (Frontiers Appl. Math. Stat., 2024)

Random vector functional link networks for function approximation on manifolds. - Deanna Needell; Aaron A. Nelson; Rayan Saab; Palina Salanevich; Olov Schavemaker (Frontiers Appl. Math. Stat., 2024)

Randomized Kaczmarz in Adversarial Distributed Setting. - Longxiu Huang; Xia Li; Deanna Needell (SIAM J. Sci. Comput., 2024)

Robust Tensor CUR Decompositions: Rapid Low-Tucker-Rank Tensor Recovery with Sparse Corruptions. - HanQin Cai; Zehan Chao; Longxiu Huang; Deanna Needell (SIAM J. Imaging Sci., 2024)

Federated Gradient Matching Pursuit. - Halyun Jeong; Deanna Needell; Jing Qin 003 (IEEE Trans. Inf. Theory, 2024)

Harnessing the Power of Sample Abundance: Theoretical Guarantees and Algorithms for Accelerated One-Bit Sensing. - Arian Eamaz; Farhang Yeganegi; Deanna Needell; Mojtaba Soltanalian (IEEE Trans. Inf. Theory, 2024)

Linear Discriminant Analysis with the Randomized Kaczmarz Method. - Jocelyn T. Chi; Deanna Needell (SIAM J. Matrix Anal. Appl., 2025)

Linear Convergence of Reshuffling Kaczmarz Methods with Sparse Constraints. - Halyun Jeong; Deanna Needell (SIAM J. Sci. Comput., 2025)

Randomized Kaczmarz Methods with Beyond-Krylov Convergence. - Michal Derezinski; Deanna Needell; Elizaveta Rebrova; Jiaming Yang (CoRR, 2025)

Curvature Corrected Nonnegative Manifold Data Factorization. - Joyce A. Chew; Willem Diepeveen; Deanna Needell (CoRR, 2025)

Cauchy Random Features for Operator Learning in Sobolev Space. - Chunyang Liao; Deanna Needell; Hayden Schaeffer (CoRR, 2025)

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)

Manifold Learning with Normalizing Flows: Towards Regularity, Expressivity and Iso-Riemannian Geometry. - Willem Diepeveen; Deanna Needell (CoRR, 2025)

A federated Kaczmarz algorithm. - Halyun Jeong; Deanna Needell; Chi-Hao Wu 001 (CoRR, 2025)

Convergence of the alternating least squares algorithm for CP tensor decompositions. - Nicholas Hu; Mark A. Iwen; Deanna Needell; Rongrong Wang (CoRR, 2025)

Observational Multiplicity. - Erin George; Deanna Needell; Berk Ustun (CoRR, 2025)