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ORCIDDeanna Needell
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- affiliation: University of California, Los Angeles, Department of Mathematic, CA, USA
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2020 – today
- 2024
[j47]HanQin Cai
, Zehan Chao, Longxiu Huang, Deanna Needell:
Robust Tensor CUR Decompositions: Rapid Low-Tucker-Rank Tensor Recovery with Sparse Corruptions. SIAM J. Imaging Sci. 17(1): 225-247 (2024)- [j46]Longxiu Huang, Xia Li, Deanna Needell:
Randomized Kaczmarz in Adversarial Distributed Setting. SIAM J. Sci. Comput. 46(3): 354- (2024) - [j45]Halyun Jeong, Deanna Needell, Jing Qin:
Federated Gradient Matching Pursuit. IEEE Trans. Inf. Theory 70(6): 4512-4537 (2024) - [j44]Arian Eamaz, Farhang Yeganegi, Deanna Needell, Mojtaba Soltanalian:
Harnessing the Power of Sample Abundance: Theoretical Guarantees and Algorithms for Accelerated One-Bit Sensing. IEEE Trans. Inf. Theory 70(9): 6690-6713 (2024) - [c54]Yuchen Li, Laura Balzano, Deanna Needell, Hanbaek Lyu:
Convergence and Complexity Guarantee for Inexact First-order Riemannian Optimization Algorithms. ICML 2024 - [i121]Halyun Jeong, Deanna Needell, Elizaveta Rebrova:
Stochastic gradient descent for streaming linear and rectified linear systems with Massart noise. CoRR abs/2403.01204 (2024) - [i120]Kedar Karhadkar, Erin George, Michael Murray, Guido Montúfar, Deanna Needell:
Benign overfitting in leaky ReLU networks with moderate input dimension. CoRR abs/2403.06903 (2024) - [i119]Ziyuan Lin, Deanna Needell:
Kernel Alignment for Unsupervised Feature Selection via Matrix Factorization. CoRR abs/2403.14688 (2024) - [i118]Michal Derezinski, Daniel LeJeune, Deanna Needell, Elizaveta Rebrova:
Fine-grained Analysis and Faster Algorithms for Iteratively Solving Linear Systems. CoRR abs/2405.05818 (2024) - [i117]Minxin Zhang, Jamie Haddock, Deanna Needell:
Block Matrix and Tensor Randomized Kaczmarz Methods for Linear Feasibility Problems. CoRR abs/2406.12021 (2024) - 2023
- [j43]Michael R. Lindstrom, Xiaofu Ding, Feng Liu, Anand Somayajula, Deanna Needell:
Continuous Semi-Supervised Nonnegative Matrix Factorization. Algorithms 16(4): 187 (2023) - [j42]Yotam Yaniv, Jacob D. Moorman, William Swartworth, Thomas K. Tu, Daji Landis, Deanna Needell:
Selectable Set Randomized Kaczmarz. Numer. Linear Algebra Appl. 30(1) (2023) - [j41]HanQin Cai, Longxiu Huang, Pengyu Li, Deanna Needell:
Matrix Completion With Cross-Concentrated Sampling: Bridging Uniform Sampling and CUR Sampling. IEEE Trans. Pattern Anal. Mach. Intell. 45(8): 10100-10113 (2023) - [c53]James Chapman, Yotam Yaniv, Deanna Needell:
Stratified-NMF for Heterogeneous Data. ACSSC 2023: 614-618 - [c52]Rachel Grotheer, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Stochastic Natural Thresholding Algorithms. ACSSC 2023: 832-836 - [c51]Shuang Li, William J. Swartworth, Martin Takác, Deanna Needell, Robert M. Gower:
SP2 : A Second Order Stochastic Polyak Method. ICLR 2023 - [c50]Arian Eamaz, Farhang Yeganegi, Deanna Needell, Mojtaba Soltanalian:
One-Bit Quadratic Compressed Sensing: From Sample Abundance to Linear Feasibility. ISIT 2023: 1154-1159 - [c49]Erin George, Michael Murray, William Swartworth, Deanna Needell:
Training shallow ReLU networks on noisy data using hinge loss: when do we overfit and is it benign? NeurIPS 2023 - [c48]William Swartworth, Deanna Needell, Rachel A. Ward, Mark Kong, Halyun Jeong:
Nearly Optimal Bounds for Cyclic Forgetting. NeurIPS 2023 - [i116]Halyun Jeong, Deanna Needell, Jing Qin:
Federated Gradient Matching Pursuit. CoRR abs/2302.10755 (2023) - [i115]Longxiu Huang, Xia Li, Deanna Needell:
Distributed Randomized Kaczmarz for the Adversarial Workers. CoRR abs/2302.14615 (2023) - [i114]Tyler Will, Runyu Zhang, Eli Sadovnik, Mengdi Gao, Joshua Vendrow, Jamie Haddock, Denali Molitor, Deanna Needell:
Neural Nonnegative Matrix Factorization for Hierarchical Multilayer Topic Modeling. CoRR abs/2303.00058 (2023) - [i113]Arian Eamaz, Farhang Yeganegi, Deanna Needell, Mojtaba Soltanalian:
One-Bit Quadratic Compressed Sensing: From Sample Abundance to Linear Feasibility. CoRR abs/2303.09594 (2023) - [i112]Halyun Jeong, Deanna Needell:
Linear Convergence of Reshuffling Kaczmarz Methods With Sparse Constraints. CoRR abs/2304.10123 (2023) - [i111]HanQin Cai, Zehan Chao, Longxiu Huang, Deanna Needell:
Robust Tensor CUR Decompositions: Rapid Low-Tucker-Rank Tensor Recovery with Sparse Corruption. CoRR abs/2305.04080 (2023) - [i110]Erin George, Joyce A. Chew, Deanna Needell:
Detecting and Mitigating Indirect Stereotypes in Word Embeddings. CoRR abs/2305.14574 (2023) - [i109]Willem Diepeveen, Joyce A. Chew, Deanna Needell:
Curvature corrected tangent space-based approximation of manifold-valued data. CoRR abs/2306.00507 (2023) - [i108]Rachel Grotheer, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Stochastic Natural Thresholding Algorithms. CoRR abs/2306.04730 (2023) - [i107]Erin George, Michael Murray, William Swartworth, Deanna Needell:
Training shallow ReLU networks on noisy data using hinge loss: when do we overfit and is it benign? CoRR abs/2306.09955 (2023) - [i106]Joyce A. Chew, Edward De Brouwer, Smita Krishnaswamy, Deanna Needell, Michael Perlmutter:
Manifold Filter-Combine Networks. CoRR abs/2307.04056 (2023) - [i105]Arian Eamaz, Farhang Yeganegi, Deanna Needell, Mojtaba Soltanalian:
Harnessing the Power of Sample Abundance: Theoretical Guarantees and Algorithms for Accelerated One-Bit Sensing. CoRR abs/2308.00695 (2023) - [i104]Cullen Haselby, Mark A. Iwen, Deanna Needell, Elizaveta Rebrova, William Swartworth:
Fast and Low-Memory Compressive Sensing Algorithms for Low Tucker-Rank Tensor Approximation from Streamed Measurements. CoRR abs/2308.13709 (2023) - [i103]James Chapman, Yotam Yaniv, Deanna Needell:
Stratified-NMF for Heterogeneous Data. CoRR abs/2311.10789 (2023) - 2022
- [j40]Pengyu Li, Christine Tseng, Yaxuan Zheng, Joyce A. Chew, Longxiu Huang, Benjamin Jarman, Deanna Needell:
Guided Semi-Supervised Non-Negative Matrix Factorization. Algorithms 15(5): 136 (2022) - [j39]Hanbaek Lyu, Christopher Strohmeier, Deanna Needell:
Online Nonnegative CP-dictionary Learning for Markovian Data. J. Mach. Learn. Res. 23: 148:1-148:50 (2022) - [j38]Jamie Haddock, Deanna Needell, Elizaveta Rebrova, William Swartworth:
Quantile-Based Iterative Methods for Corrupted Systems of Linear Equations. SIAM J. Matrix Anal. Appl. 43(2): 605-637 (2022) - [j37]Abigail Hickok, Deanna Needell, Mason A. Porter:
Analysis of Spatial and Spatiotemporal Anomalies Using Persistent Homology: Case Studies with COVID-19 Data. SIAM J. Math. Data Sci. 4(3): 1116-1144 (2022) - [c47]Benjamin Jarman, Yotam Yaniv, Deanna Needell:
Online Signal Recovery via Heavy Ball Kaczmarz. IEEECONF 2022: 276-280 - [c46]Erin George, Yotam Yaniv, Deanna Needell:
Multi-Randomized Kaczmarz for Latent Class Regression. IEEECONF 2022: 1367-1371 - [c45]Xiaofu Ding, Xinyu Dong, Olivia McGough, Chenxin Shen, Annie Ulichney, Ruiyao Xu, William Swartworth, Jocelyn T. Chi, Deanna Needell:
Population-Based Hierarchical Non-Negative Matrix Factorization for Survey Data. BDCAT 2022: 184-193 - [c44]Andrew Sack, Wenzhao Jiang, Michael Perlmutter, Palina Salanevich, Deanna Needell:
On Audio Enhancement via Online Non-Negative Matrix Factorization. CISS 2022: 287-291 - [c43]Deanna Needell, William Swartworth, David P. Woodruff:
Testing Positive Semidefiniteness Using Linear Measurements. FOCS 2022: 87-97 - [c42]Joshua Vendrow, Jamie Haddock, Deanna Needell:
A Generalized Hierarchical Nonnegative Tensor Decomposition. ICASSP 2022: 4473-4477 - [c41]Joyce A. Chew, Holly R. Steach, Siddharth Viswanath, Hau-Tieng Wu, Matthew J. Hirn, Deanna Needell, Matthew D. Vesely, Smita Krishnaswamy, Michael Perlmutter:
The Manifold Scattering Transform for High-Dimensional Point Cloud Data. TAG-ML 2022: 67-78 - [i102]Pengyu Li, Christine Tseng, Yaxuan Zheng, Joyce A. Chew, Longxiu Huang, Benjamin Jarman, Deanna Needell:
Guided Semi-Supervised Non-negative Matrix Factorization on Legal Documents. CoRR abs/2201.13324 (2022) - [i101]Xia Li, Longxiu Huang, Deanna Needell:
Distributed randomized Kaczmarz for the adversarial workers. CoRR abs/2203.00095 (2022) - [i100]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:
Semi-supervised Nonnegative Matrix Factorization for Document Classification. CoRR abs/2203.03551 (2022) - [i99]Deanna Needell, William Swartworth, David P. Woodruff:
Testing Positive Semidefiniteness Using Linear Measurements. CoRR abs/2204.03782 (2022) - [i98]Joyce A. Chew, Holly R. Steach, Siddharth Viswanath, Hau-Tieng Wu, Matthew J. Hirn, Deanna Needell, Smita Krishnaswamy, Michael Perlmutter:
The Manifold Scattering Transform for High-Dimensional Point Cloud Data. CoRR abs/2206.10078 (2022) - [i97]Lu Cheng, Benjamin Jarman, Deanna Needell, Elizaveta Rebrova:
On Block Accelerations of Quantile Randomized Kaczmarz for Corrupted Systems of Linear Equations. CoRR abs/2206.12554 (2022) - [i96]Shuang Li, William J. Swartworth, Martin Takác, Deanna Needell, Robert M. Gower:
SP2: A Second Order Stochastic Polyak Method. CoRR abs/2207.08171 (2022) - [i95]Joyce A. Chew, Matthew J. Hirn, Smita Krishnaswamy, Deanna Needell, Michael Perlmutter, Holly R. Steach, Siddharth Viswanath, Hau-Tieng Wu:
Geometric Scattering on Measure Spaces. CoRR abs/2208.08561 (2022) - [i94]HanQin Cai, Longxiu Huang, Pengyu Li, Deanna Needell:
Matrix Completion with Cross-Concentrated Sampling: Bridging Uniform Sampling and CUR Sampling. CoRR abs/2208.09723 (2022) - [i93]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, Chuntian Wang, Megan Coffee, Kathryn Leonard, Deanna Needell:
Automatic Infectious Disease Classification Analysis with Concept Discovery. CoRR abs/2209.02415 (2022) - [i92]Benjamin Jarman, Yotam Yaniv, Deanna Needell:
Online Signal Recovery via Heavy Ball Kaczmarz. CoRR abs/2211.06391 (2022) - [i91]Zehan Chao, Denali Molitor, Deanna Needell, Mason A. Porter:
Inference of Media Bias and Content Quality Using Natural-Language Processing. CoRR abs/2212.00237 (2022) - [i90]Erin George, Yotam Yaniv, Deanna Needell:
Multi-Randomized Kaczmarz for Latent Class Regression. CoRR abs/2212.03962 (2022) - [i89]Michael R. Lindstrom, Xiaofu Ding, Feng Liu, Anand Somayajula, Deanna Needell:
Continuous Semi-Supervised Nonnegative Matrix Factorization. CoRR abs/2212.09858 (2022) - [i88]Joyce A. Chew, Deanna Needell, Michael Perlmutter:
A Convergence Rate for Manifold Neural Networks. CoRR abs/2212.12606 (2022) - 2021
- [j36]Jesús A. De Loera, Jamie Haddock, Anna Ma, Deanna Needell:
Data-driven algorithm selection and tuning in optimization and signal processing. Ann. Math. Artif. Intell. 89(7): 711-735 (2021) - [j35]Zehan Chao, Longxiu Huang, Deanna Needell:
HOSVD-Based Algorithm for Weighted Tensor Completion. J. Imaging 7(7): 110 (2021) - [j34]HanQin Cai, Keaton Hamm, Longxiu Huang, Deanna Needell:
Mode-wise Tensor Decompositions: Multi-dimensional Generalizations of CUR Decompositions. J. Mach. Learn. Res. 22: 185:1-185:36 (2021) - [j33]Elizaveta Rebrova, Deanna Needell:
On block Gaussian sketching for the Kaczmarz method. Numer. Algorithms 86(1): 443-473 (2021) - [j32]HanQin Cai, Keaton Hamm, Longxiu Huang, Deanna Needell:
Robust CUR Decomposition: Theory and Imaging Applications. SIAM J. Imaging Sci. 14(4): 1472-1503 (2021) - [j31]Mark A. Iwen, Deanna Needell, Elizaveta Rebrova, Ali Zare:
Lower Memory Oblivious (Tensor) Subspace Embeddings with Fewer Random Bits: Modewise Methods for Least Squares. SIAM J. Matrix Anal. Appl. 42(1): 376-416 (2021) - [j30]Robert M. Gower, Denali Molitor, Jacob D. Moorman, Deanna Needell:
On Adaptive Sketch-and-Project for Solving Linear Systems. SIAM J. Matrix Anal. Appl. 42(2): 954-989 (2021) - [j29]Simon Foucart, Deanna Needell, Reese Pathak, Yaniv Plan, Mary Wootters:
Weighted Matrix Completion From Non-Random, Non-Uniform Sampling Patterns. IEEE Trans. Inf. Theory 67(2): 1264-1290 (2021) - [c40]Shuang Li, Deanna Needell, William Swartworth:
An Untrained One-layer Convolutional Network-based Method for Line Spectral Estimation. ACSCC 2021: 795-799 - [c39]Benjamin Jarman, Deanna Needell:
QuantileRK: Solving Large-Scale Linear Systems with Corrupted, Noisy Data. ACSCC 2021: 1312-1316 - [c38]Joshua Vendrow, Jamie Haddock, Deanna Needell:
Neural Nonnegative CP Decomposition for Hierarchical Tensor Analysis. ACSCC 2021: 1340-1347 - [c37]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:
Semi-supervised Nonnegative Matrix Factorization for Document Classification. ACSCC 2021: 1355-1360 - [c36]Joshua Vendrow, Jamie Haddock, Elizaveta Rebrova, Deanna Needell:
On a Guided Nonnegative Matrix Factorization. ICASSP 2021: 3265-32369 - [c35]HanQin Cai, Zehan Chao, Longxiu Huang, Deanna Needell:
Fast Robust Tensor Principal Component Analysis via Fiber CUR Decomposition *. ICCVW 2021: 189-197 - [c34]Michael R. Lindstrom, William J. Swartworth, Deanna Needell:
Reconstructing Piezoelectric Responses over a Lattice: Adaptive Sampling of Low Dimensional Time Series Representations Based on Relative Isolation and Gradient Size. SMC 2021: 420-429 - [i87]HanQin Cai, Keaton Hamm, Longxiu Huang, Deanna Needell:
Robust CUR Decomposition: Theory and Imaging Applications. CoRR abs/2101.05231 (2021) - [i86]HanQin Cai, Keaton Hamm, Longxiu Huang, Deanna Needell:
Mode-wise Tensor Decompositions: Multi-dimensional Generalizations of CUR Decompositions. CoRR abs/2103.11037 (2021) - [i85]Ryan Budahazy, Lu Cheng, Yihuan Huang, Andrew Johnson, Pengyu Li, Joshua Vendrow, Zhoutong Wu, Denali Molitor, Elizaveta Rebrova, Deanna Needell:
Analysis of Legal Documents via Non-negative Matrix Factorization Methods. CoRR abs/2104.14028 (2021) - [i84]Abigail Hickok, Deanna Needell, Mason A. Porter:
Analysis of Spatiotemporal Anomalies Using Persistent Homology: Case Studies with COVID-19 Data. CoRR abs/2107.09188 (2021) - [i83]Benjamin Jarman, Deanna Needell:
QuantileRK: Solving Large-Scale Linear Systems with Corrupted, Noisy Data. CoRR abs/2108.02304 (2021) - [i82]HanQin Cai, Zehan Chao, Longxiu Huang, Deanna Needell:
Fast Robust Tensor Principal Component Analysis via Fiber CUR Decomposition. CoRR abs/2108.10448 (2021) - [i81]Mark A. Iwen, Deanna Needell, Michael Perlmutter, Elizaveta Rebrova:
Modewise Operators, the Tensor Restricted Isometry Property, and Low-Rank Tensor Recovery. CoRR abs/2109.10454 (2021) - [i80]Longxiu Huang, Deanna Needell, Sui Tang:
Robust recovery of bandlimited graph signals via randomized dynamical sampling. CoRR abs/2109.14079 (2021) - [i79]Joshua Vendrow, Jamie Haddock, Deanna Needell:
A Generalized Hierarchical Nonnegative Tensor Decomposition. CoRR abs/2109.14820 (2021) - [i78]Andrew Sack, Wenzhao Jiang, Michael Perlmutter, Palina Salanevich, Deanna Needell:
On audio enhancement via online non-negative matrix factorization. CoRR abs/2110.03114 (2021) - [i77]Yotam Yaniv, Jacob D. Moorman, William Swartworth, Thomas K. Tu, Daji Landis, Deanna Needell:
Selectable Set Randomized Kaczmarz. CoRR abs/2110.04703 (2021) - 2020
- [j28]Joshua Vendrow, Jamie Haddock, Deanna Needell, Lorraine Johnson:
Feature Selection from Lyme Disease Patient Survey Using Machine Learning. Algorithms 13(12): 334 (2020) - [c33]Lara Kassab, Henry Adams, Deanna Needell:
An Adaptation for Iterative Structured Matrix Completion. ACSSC 2020: 1451-1456 - [c32]Jamie Haddock, Deanna Needell, Elizaveta Rebrova, William Swartworth:
Stochastic Gradient Descent Variants for Corrupted Systems of Linear Equations. CISS 2020: 1-6 - [c31]Rachel Grotheer, Longxiu Huang, Yihuan Huang, Alona Kryshchenko, Oleksandr Kryshchenko, Pengyu Li, Xia Li, Elizaveta Rebrova, Kyung Ha, Deanna Needell:
COVID-19 Literature Topic-Based Search via Hierarchical NMF. NLP4COVID@EMNLP 2020 - [c30]Christopher Strohmeier, Deanna Needell:
Clustering of Nonnegative Data and an Application to Matrix Completion. ICASSP 2020: 8349-8353 - [c29]Zehan Chao, Longxiu Huang, Deanna Needell:
Tensor Completion through Total Variation with Initialization from Weighted HOSVD. ITA 2020: 1-8 - [c28]Rachel Grotheer, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Stochastic Iterative Hard Thresholding for Low-Tucker-Rank Tensor Recovery. ITA 2020: 1-5 - [c27]Jamie Haddock, Lara Kassab, Alona Kryshchenko, Deanna Needell:
On Nonnegative CP Tensor Decomposition Robustness to Noise. ITA 2020: 1-7 - [c26]Hanbaek Lyu, Georg Menz, Deanna Needell, Christopher Strohmeier:
Applications of Online Nonnegative Matrix Factorization to Image and Time-Series Data. ITA 2020: 1-9 - [i76]Miju Ahn, Nicole Eikmeier, Jamie Haddock, Lara Kassab, Alona Kryshchenko, Kathryn Leonard, Deanna Needell, R. W. M. A. Madushani, Elena Sizikova, Chuntian Wang:
On Large-Scale Dynamic Topic Modeling with Nonnegative CP Tensor Decomposition. CoRR abs/2001.00631 (2020) - [i75]Henry Adams, Lara Kassab, Deanna Needell:
An Iterative Method for Structured Matrix Completion. CoRR abs/2002.02041 (2020) - [i74]Jacob D. Moorman, Thomas K. Tu, Denali Molitor, Deanna Needell:
Randomized Kaczmarz with Averaging. CoRR abs/2002.04126 (2020) - [i73]Longxiu Huang, Deanna Needell:
HOSVD-Based Algorithm for Weighted Tensor Completion. CoRR abs/2003.08537 (2020) - [i72]Zehan Chao, Longxiu Huang, Deanna Needell:
Tensor Completion through Total Variationwith Initialization from Weighted HOSVD. CoRR abs/2003.09062 (2020) - [i71]Hanbaek Lyu, Christopher Strohmeier, Georg Menz, Deanna Needell:
COVID-19 Time-series Prediction by Joint Dictionary Learning and Online NMF. CoRR abs/2004.09112 (2020) - [i70]Deanna Needell, Aaron A. Nelson, Rayan Saab, Palina Salanevich:
Random Vector Functional Link Networks for Function Approximation on Manifolds. CoRR abs/2007.15776 (2020) - [i69]Christopher Strohmeier, Deanna Needell:
Clustering of Nonnegative Data and an Application to Matrix Completion. CoRR abs/2009.01279 (2020) - [i68]Christopher Strohmeier, Hanbaek Lyu, Deanna Needell:
Online nonnegative tensor factorization and CP-dictionary learning for Markovian data. CoRR abs/2009.07612 (2020) - [i67]Jamie Haddock, Deanna Needell, Elizaveta Rebrova, William Swartworth:
Quantile-based Iterative Methods for Corrupted Systems of Linear Equations. CoRR abs/2009.08089 (2020) - [i66]Rachel Grotheer, Yihuan Huang, Pengyu Li, Elizaveta Rebrova, Deanna Needell, Longxiu Huang, Alona Kryshchenko, Xia Li, Kyung Ha, Oleksandr Kryshchenko:
COVID-19 Literature Topic-Based Search via Hierarchical NMF. CoRR abs/2009.09074 (2020) - [i65]Joshua Vendrow, Jamie Haddock, Deanna Needell, Lorraine Johnson:
Feature Selection on Lyme Disease Patient Survey Data. CoRR abs/2009.09087 (2020) - [i64]Lara Kassab, Alona Kryshchenko, Hanbaek Lyu, Denali Molitor, Deanna Needell, Elizaveta Rebrova:
On Nonnegative Matrix and Tensor Decompositions for COVID-19 Twitter Dynamics. CoRR abs/2010.01600 (2020) - [i63]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:
Semi-supervised NMF Models for Topic Modeling in Learning Tasks. CoRR abs/2010.07956 (2020) - [i62]Joshua Vendrow, Jamie Haddock, Elizaveta Rebrova, Deanna Needell:
On a Guided Nonnegative Matrix Factorization. CoRR abs/2010.11365 (2020) - [i61]Hanbaek Lyu, Georg Menz, Deanna Needell, Christopher Strohmeier:
Applications of Online Nonnegative Matrix Factorization to Image and Time-Series Data. CoRR abs/2011.05384 (2020)
2010 – 2019
- 2019
- [j27]Denali Molitor, Deanna Needell:
Hierarchical Classification Using Binary Data. AI Mag. 40(2): 59-65 (2019) - [j26]Lenny Fukshansky, Deanna Needell, Benny Sudakov:
An algebraic perspective on integer sparse recovery. Appl. Math. Comput. 340: 31-42 (2019) - [j25]Lenny Fukshansky, Deanna Needell, Josiah Park, Yuxin Xin:
Lattices From Tight Frames and Vertex Transitive Graphs. Electron. J. Comb. 26(3): 3 (2019) - [j24]Tong Wu, Yicang Zhou, Yanni Xiao, Deanna Needell, Feiping Nie:
Modified fuzzy clustering with segregated cluster centroids. Neurocomputing 361: 10-18 (2019) - [j23]Jamie Haddock, Deanna Needell:
Randomized Projection Methods for Linear Systems with Arbitrarily Large Sparse Corruptions. SIAM J. Sci. Comput. 41(5): S19-S36 (2019) - [j22]Anna Ma, You Joe Zhou, Cynthia Rush, Dror Baron, Deanna Needell:
An Approximate Message Passing Framework for Side Information. IEEE Trans. Signal Process. 67(7): 1875-1888 (2019) - [c25]Elizaveta Rebrova, Deanna Needell:
Sketching for Motzkin's Iterative Method for Linear Systems. ACSSC 2019: 271-275 - [c24]Jamie Haddock, Deanna Needell, Alireza Zaeemzadeh, Nazanin Rahnavard:
Convergence of Iterative Hard Thresholding Variants with Application to Asynchronous Parallel Methods for Sparse Recovery. ACSSC 2019: 276-279 - [c23]Natalie Durgin, Rachel Grotheer, Chenxi Huang, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Jointly Sparse Signal Recovery with Prior Info. ACSSC 2019: 645-649 - [c22]Mengdi Gao, Jamie Haddock, Denali Molitor, Deanna Needell, Eli Sadovnik, Tyler Will, Runyu Zhang:
Neural Nonnegative Matrix Factorization for Hierarchical Multilayer Topic Modeling. CAMSAP 2019: 6-10 - [c21]Jyun-Yu Jiang, Zehan Chao, Andrea L. Bertozzi, Wei Wang, Sean D. Young, Deanna Needell:
Learning to Predict Human Stress Level with Incomplete Sensor Data from Wearable Devices. CIKM 2019: 2773-2781 - [c20]Natalie Durgin, Rachel Grotheer, Chenxi Huang, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Fast Hyperspectral Diffuse Optical Imaging Method with Joint Sparsity. EMBC 2019: 4758-4761 - [i60]Christian Parkinson, Kevin Huynh, Deanna Needell:
Matrix Completion With Selective Sampling. CoRR abs/1904.08540 (2019) - [i59]Jesús A. De Loera, Jamie Haddock, Anna Ma, Deanna Needell:
Data-driven Algorithm Selection and Parameter Tuning: Two Case studies in Optimization and Signal Processing. CoRR abs/1905.13404 (2019) - [i58]Denali Molitor, Deanna Needell, Rachel A. Ward:
Bias of Homotopic Gradient Descent for the Hinge Loss. CoRR abs/1907.11746 (2019) - [i57]Rachel Grotheer, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Iterative Hard Thresholding for Low CP-rank Tensor Models. CoRR abs/1908.08479 (2019) - [i56]Robert M. Gower, Denali Molitor, Jacob D. Moorman, Deanna Needell:
Adaptive Sketch-and-Project Methods for Solving Linear Systems. CoRR abs/1909.03604 (2019) - [i55]Rachel Grotheer, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Stochastic Iterative Hard Thresholding for Low-Tucker-Rank Tensor Recovery. CoRR abs/1909.10132 (2019) - [i54]Simon Foucart, Deanna Needell, Reese Pathak, Yaniv Plan, Mary Wootters:
Weighted matrix completion from non-random, non-uniform sampling patterns. CoRR abs/1910.13986 (2019) - [i53]Hanbaek Lyu, Deanna Needell, Laura Balzano:
Online matrix factorization for Markovian data and applications to Network Dictionary Learning. CoRR abs/1911.01931 (2019) - [i52]Yuchen Guo, Nicholas Hanoian, Zhexiao Lin, Nicholas Liskij, Hanbaek Lyu, Deanna Needell, Jiahao Qu, Henry Sojico, Yuliang Wang, Zhe Xiong, Zhenhong Zou:
Topic-aware chatbot using Recurrent Neural Networks and Nonnegative Matrix Factorization. CoRR abs/1912.00315 (2019) - [i51]Elizaveta Rebrova, Deanna Needell:
Sketching for Motzkin's Iterative Method for Linear Systems. CoRR abs/1912.00771 (2019) - [i50]Mark A. Iwen, Deanna Needell, Elizaveta Rebrova, Ali Zare:
Lower Memory Oblivious (Tensor) Subspace Embeddings with Fewer Random Bits: Modewise Methods for Least Squares. CoRR abs/1912.08294 (2019) - 2018
- [j21]Deanna Needell, Rayan Saab, Tina Woolf:
Simple Classification Using Binary Data. J. Mach. Learn. Res. 19: 61:1-61:30 (2018) - [j20]Anna Ma, Deanna Needell, Aaditya Ramdas:
Iterative Methods for Solving Factorized Linear Systems. SIAM J. Matrix Anal. Appl. 39(1): 104-122 (2018) - [j19]Xiaoyi Gu, Shenyinying Tu, Hao-Jun Michael Shi, Mindy Case, Deanna Needell, Yaniv Plan:
Optimizing Quantization for Lasso Recovery. IEEE Signal Process. Lett. 25(1): 45-49 (2018) - [c19]Anna Ma, Deanna Needell:
A Gradient Descent Approach for Incomplete Linear Systems. ACSSC 2018: 764-768 - [c18]Alireza Zaeemzadeh, Jamie Haddock, Nazanin Rahnavard, Deanna Needell:
A Bayesian Approach for Asynchronous Parallel Sparse Recovery. ACSSC 2018: 1980-1984 - [c17]Denali Molitor, Deanna Needell:
Matrix Completion for Structured Observations. ITA 2018: 1-5 - [c16]Saiprasad Ravishankar, Anna Ma, Deanna Needell:
Analysis of Fast Alternating Minimization for Structured Dictionary Learning. ITA 2018: 1-9 - [i49]Denali Molitor, Deanna Needell:
Matrix Completion for Structured Observations. CoRR abs/1801.09657 (2018) - [i48]Natalie Durgin, Rachel Grotheer, Chenxi Huang, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Compressed Anomaly Detection with Multiple Mixed Observations. CoRR abs/1801.10264 (2018) - [i47]Saiprasad Ravishankar, Anna Ma, Deanna Needell:
Analysis of Fast Alternating Minimization for Structured Dictionary Learning. CoRR abs/1802.00518 (2018) - [i46]Jamie Haddock, Deanna Needell:
Randomized Projection Methods for Corrupted Linear Systems. CoRR abs/1803.08114 (2018) - [i45]Saiprasad Ravishankar, Anna Ma, Deanna Needell:
Analysis of Fast Structured Dictionary Learning. CoRR abs/1805.12529 (2018) - [i44]Anna Ma, You Joe Zhou, Cynthia Rush, Dror Baron, Deanna Needell:
An Approximate Message Passing Framework for Side Information. CoRR abs/1807.04839 (2018) - [i43]Denali Molitor, Deanna Needell:
Hierarchical Classification using Binary Data. CoRR abs/1807.08825 (2018) - [i42]Denali Molitor, Deanna Needell:
An iterative method for classification of binary data. CoRR abs/1809.03041 (2018) - 2017
- [j18]Ahmed Hefny, Deanna Needell, Aaditya Ramdas:
Rows versus Columns: Randomized Kaczmarz or Gauss-Seidel for Ridge Regression. SIAM J. Sci. Comput. 39(5) (2017) - [j17]Jesús A. De Loera, Jamie Haddock, Deanna Needell:
A Sampling Kaczmarz-Motzkin Algorithm for Linear Feasibility. SIAM J. Sci. Comput. 39(5) (2017) - [j16]Richard G. Baraniuk, Simon Foucart, Deanna Needell, Yaniv Plan, Mary Wootters:
Exponential Decay of Reconstruction Error From Binary Measurements of Sparse Signals. IEEE Trans. Inf. Theory 63(6): 3368-3385 (2017) - [j15]Nam Nguyen, Deanna Needell, Tina Woolf:
Linear Convergence of Stochastic Iterative Greedy Algorithms With Sparse Constraints. IEEE Trans. Inf. Theory 63(11): 6869-6895 (2017) - [c15]Deanna Needell, Rayan Saab, Tina Woolf:
Simple Object Classification Using Binary Data. AAAI Fall Symposia 2017: 218-224 - [c14]Dror Baron, Anna Ma, Deanna Needell, Cynthia Rush, Tina Woolf:
Conditional approximate message passing with side information. ACSSC 2017: 430-434 - [c13]Deanna Needell, Tina Woolf:
An asynchronous parallel approach to sparse recovery. ITA 2017: 1-5 - [i41]Deanna Needell, Tina Woolf:
An Asynchronous Parallel Approach to Sparse Recovery. CoRR abs/1701.03458 (2017) - [i40]Deanna Needell, Rayan Saab, Tina Woolf:
Simple Classification using Binary Data. CoRR abs/1707.01945 (2017) - [i39]Jing Qin, Shuang Li, Deanna Needell, Anna Ma, Rachel Grotheer, Chenxi Huang, Natalie Durgin:
Stochastic Greedy Algorithms For Multiple Measurement Vectors. CoRR abs/1711.01521 (2017) - [i38]Natalie Durgin, Rachel Grotheer, Chenxi Huang, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Sparse Randomized Kaczmarz for Support Recovery of Jointly Sparse Corrupted Multiple Measurement Vectors. CoRR abs/1711.02743 (2017) - 2016
- [j14]Deanna Needell, Nathan Srebro, Rachel A. Ward:
Stochastic gradient descent, weighted sampling, and the randomized Kaczmarz algorithm. Math. Program. 155(1-2): 549-573 (2016) - [j13]Mark A. Davenport, Andrew K. Massimino, Deanna Needell, Tina Woolf:
Constrained Adaptive Sensing. IEEE Trans. Signal Process. 64(20): 5437-5449 (2016) - [c12]Hao-Jun Michael Shi, Mindy Case, Xiaoyi Gu, Shenyinying Tu, Deanna Needell:
Methods for quantized compressed sensing. ITA 2016: 1-9 - [i37]Deanna Needell, Rayan Saab, Tina Woolf:
Weighted ℓ1-Minimization for Sparse Recovery under Arbitrary Prior Information. CoRR abs/1606.01295 (2016) - [i36]Xiaoyi Gu, Shenyinying Tu, Hao-Jun Michael Shi, Mindy Case, Deanna Needell, Yaniv Plan:
Optimizing quantization for Lasso recovery. CoRR abs/1606.03055 (2016) - [i35]Richard G. Baraniuk, Simon Foucart, Deanna Needell, Yaniv Plan, Mary Wootters:
One-Bit Compressive Sensing of Dictionary-Sparse Signals. CoRR abs/1606.07531 (2016) - [i34]Samuel Birns, Bohyun Kim, Stephanie Ku, Kevin Stangl, Deanna Needell:
A Practical Study of Longitudinal Reference Based Compressed Sensing for MRI. CoRR abs/1608.04728 (2016) - [i33]Tobias Birnbaum, Yonina C. Eldar, Deanna Needell:
Tolerant Compressed Sensing With Partially Coherent Sensing Matrices. CoRR abs/1608.05094 (2016) - [i32]Deanna Needell, Rachel A. Ward:
Batched Stochastic Gradient Descent with Weighted Sampling. CoRR abs/1608.07641 (2016) - 2015
- [j12]Raja Giryes, Deanna Needell:
Near oracle performance and block analysis of signal space greedy methods. J. Approx. Theory 194: 157-174 (2015) - [j11]Jonathan Briskman, Deanna Needell:
Block Kaczmarz Method with Inequalities. J. Math. Imaging Vis. 52(3): 385-396 (2015) - [j10]Felix Krahmer, Deanna Needell, Rachel A. Ward:
Compressive Sensing with Redundant Dictionaries and Structured Measurements. SIAM J. Math. Anal. 47(6): 4606-4629 (2015) - [j9]Anna Ma, Deanna Needell, Aaditya Ramdas:
Convergence Properties of the Randomized Extended Gauss-Seidel and Kaczmarz Methods. SIAM J. Matrix Anal. Appl. 36(4): 1590-1604 (2015) - [c11]Phillip North, Deanna Needell:
One-bit Compressive Sensing with partial support. CAMSAP 2015: 349-352 - [i31]Felix Krahmer, Deanna Needell, Rachel A. Ward:
Compressive Sensing with Redundant Dictionaries and Structured Measurements. CoRR abs/1501.03208 (2015) - [i30]Phillip North, Deanna Needell:
One-Bit Compressive Sensing with Partial Support. CoRR abs/1506.00998 (2015) - [i29]Mark A. Davenport, Andrew K. Massimino, Deanna Needell, Tina Woolf:
Constrained adaptive sensing. CoRR abs/1506.05889 (2015) - [i28]Xiaoyi Gu, Deanna Needell, Shenyinying Tu:
A note on practical approximate projection schemes in signal space methods. CoRR abs/1511.03763 (2015) - [i27]Hao-Jun Michael Shi, Mindy Case, Xiaoyi Gu, Shenyinying Tu, Deanna Needell:
Methods for Quantized Compressed Sensing. CoRR abs/1512.09184 (2015) - 2014
- [j8]Yanting Ma, Dror Baron, Deanna Needell:
Two-Part Reconstruction With Noisy-Sudocodes. IEEE Trans. Signal Process. 62(23): 6323-6334 (2014) - [c10]Ran Zhao, Deanna Needell, Christopher Johansen, Jerry L. Grenard:
A comparison of clustering and missing data methods for health sciences. ACSSC 2014: 1041-1045 - [c9]Anna Ma, Arjuna Flenner, Deanna Needell, Allon G. Percus:
Improving image clustering using sparse text and the wisdom of the crowds. ACSSC 2014: 1555-1557 - [c8]Deanna Needell, Rachel A. Ward, Nathan Srebro:
Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm. NIPS 2014: 1017-1025 - [i26]Raja Giryes, Deanna Needell:
Near Oracle Performance of Signal Space Greedy Methods. CoRR abs/1402.2601 (2014) - [i25]Ran Zhao, Deanna Needell, Christopher Johansen, Jerry L. Grenard:
A Comparison of Clustering and Missing Data Methods for Health Sciences. CoRR abs/1404.5899 (2014) - [i24]Anna Ma, Arjuna Flenner, Deanna Needell, Allon G. Percus:
Improving Image Clustering using Sparse Text and the Wisdom of the Crowds. CoRR abs/1405.2102 (2014) - [i23]Yanting Ma, Dror Baron, Deanna Needell:
Two-Part Reconstruction with Noisy-Sudocodes. CoRR abs/1406.1569 (2014) - [i22]Nam Nguyen, Deanna Needell, Tina Woolf:
Linear Convergence of Stochastic Iterative Greedy Algorithms with Sparse Constraints. CoRR abs/1407.0088 (2014) - [i21]Richard G. Baraniuk, Simon Foucart, Deanna Needell, Yaniv Plan, Mary Wootters:
Exponential decay of reconstruction error from binary measurements of sparse signals. CoRR abs/1407.8246 (2014) - [i20]Chris Garnatz, Xiaoyi Gu, Alison Kingman, James LaManna, Deanna Needell, Shenyinying Tu:
Practical approximate projection schemes in greedy signal space methods. CoRR abs/1409.1527 (2014) - 2013
- [j7]Deanna Needell, Rachel A. Ward:
Stable Image Reconstruction Using Total Variation Minimization. SIAM J. Imaging Sci. 6(2): 1035-1058 (2013) - [j6]Deanna Needell, Rachel A. Ward:
Near-Optimal Compressed Sensing Guarantees for Total Variation Minimization. IEEE Trans. Image Process. 22(10): 3941-3949 (2013) - [j5]Mark A. Davenport, Deanna Needell, Michael B. Wakin:
Signal Space CoSaMP for Sparse Recovery With Redundant Dictionaries. IEEE Trans. Inf. Theory 59(10): 6820-6829 (2013) - [c7]Yanting Ma, Dror Baron, Deanna Needell:
Two-part reconstruction in compressed sensing. GlobalSIP 2013: 1041-1044 - [c6]Noreen Jamil, Deanna Needell, Johannes Müller, Christof Lutteroth, Gerald Weber:
Kaczmarz Algorithm with Soft Constraints for User Interface Layout. ICTAI 2013: 818-824 - [i19]Atul Divekar, Deanna Needell:
Using Correlated Subset Structure for Compressive Sensing Recovery. CoRR abs/1302.3918 (2013) - [i18]Laurent Demanet, Deanna Needell, Nam Nguyen:
Super-resolution via superset selection and pruning. CoRR abs/1302.6288 (2013) - [i17]Nathan Lenssen, Deanna Needell:
On the Mathematics of Music: From Chords to Fourier Analysis. CoRR abs/1306.2859 (2013) - [i16]Yanting Ma, Dror Baron, Deanna Needell:
Two-Part Reconstruction in Compressed Sensing. CoRR abs/1306.5776 (2013) - [i15]Raja Giryes, Deanna Needell:
Greedy Signal Space Methods for incoherence and beyond. CoRR abs/1309.2676 (2013) - [i14]Noreen Jamil, Deanna Needell, Johannes Müller, Christof Lutteroth, Gerald Weber:
Kaczmarz Algorithm with Soft Constraints for User Interface Layout. CoRR abs/1309.7001 (2013) - [i13]Deanna Needell, Nathan Srebro, Rachel A. Ward:
Stochastic gradient descent and the randomized Kaczmarz algorithm. CoRR abs/1310.5715 (2013) - [i12]Guangliang Chen, Atul Divekar, Deanna Needell:
Guaranteed sparse signal recovery with highly coherent sensing matrices. CoRR abs/1311.0314 (2013) - 2012
- [c5]Mark A. Davenport, Deanna Needell, Michael B. Wakin:
CoSaMP with redundant dictionaries. ACSCC 2012: 263-267 - [i11]Deanna Needell, Rachel A. Ward:
Stable image reconstruction using total variation minimization. CoRR abs/1202.6429 (2012) - [i10]Mark A. Davenport, Deanna Needell, Michael B. Wakin:
Signal Space CoSaMP for Sparse Recovery with Redundant Dictionaries. CoRR abs/1208.0353 (2012) - [i9]Deanna Needell, Joel A. Tropp:
Paved with Good Intentions: Analysis of a Randomized Block Kaczmarz Method. CoRR abs/1208.3805 (2012) - [i8]Deanna Needell, Rachel A. Ward:
Total variation minimization for stable multidimensional signal recovery. CoRR abs/1210.3098 (2012) - [i7]B. Cung, T. Jin, Juan Ramirez, A. Thompson, Christos Boutsidis, Deanna Needell:
Spectral Clustering: An empirical study of Approximation Algorithms and its Application to the Attrition Problem. CoRR abs/1211.3444 (2012) - 2011
- [j4]Yonina C. Eldar, Deanna Needell:
Acceleration of randomized Kaczmarz method via the Johnson-Lindenstrauss Lemma. Numer. Algorithms 58(2): 163-177 (2011) - [i6]Yonina C. Eldar, Deanna Needell, Yaniv Plan:
Unicity conditions for low-rank matrix recovery. CoRR abs/1103.5479 (2011) - 2010
- [j3]Deanna Needell, Joel A. Tropp:
CoSaMP: iterative signal recovery from incomplete and inaccurate samples. Commun. ACM 53(12): 93-100 (2010) - [j2]Deanna Needell, Roman Vershynin:
Signal Recovery From Incomplete and Inaccurate Measurements Via Regularized Orthogonal Matching Pursuit. IEEE J. Sel. Top. Signal Process. 4(2): 310-316 (2010) - [c4]Matthew A. Herman, Deanna Needell:
Mixed operators in compressed sensing. CISS 2010: 1-6 - [i5]Emmanuel J. Candès, Yonina C. Eldar, Deanna Needell:
Compressed Sensing with Coherent and Redundant Dictionaries. CoRR abs/1005.2613 (2010)
2000 – 2009
- 2009
- [j1]Deanna Needell, Roman Vershynin:
Uniform Uncertainty Principle and Signal Recovery via Regularized Orthogonal Matching Pursuit. Found. Comput. Math. 9(3): 317-334 (2009) - [i4]Deanna Needell:
Noisy Signal Recovery via Iterative Reweighted L1-Minimization. CoRR abs/0904.3780 (2009) - [i3]Deanna Needell:
Topics in Compressed Sensing. CoRR abs/0905.4482 (2009) - 2008
- [c3]Deanna Needell, Joel A. Tropp, Roman Vershynin:
Greedy signal recovery review. ACSCC 2008: 1048-1050 - [c2]Deanna Needell, Roman Vershynin:
Greedy signal recovery and uncertainty principles. Computational Imaging 2008: 68140 - [i2]Joel A. Tropp, Deanna Needell:
CoSaMP: Iterative signal recovery from incomplete and inaccurate samples. CoRR abs/0803.2392 (2008) - [i1]Deanna Needell, Joel A. Tropp, Roman Vershynin:
Greedy Signal Recovery Review. CoRR abs/0812.2202 (2008) - 2003
- [c1]Deanna Needell, Jeff A. Stuart, Tamara C. Thiel, Sergiu Dascalu, Frederick C. Harris Jr.:
Software Requirements Specification of a University Class Scheduler. Software Engineering Research and Practice 2003: 490-496
Coauthor Index
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