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ORCIDElizaveta Rebrova
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2020 – today
- 2024
[j5]Michal Derezinski, Elizaveta Rebrova:
Sharp Analysis of Sketch-and-Project Methods via a Connection to Randomized Singular Value Decomposition. SIAM J. Math. Data Sci. 6(1): 127-153 (2024)- [i21]Halyun Jeong, Deanna Needell, Elizaveta Rebrova:
Stochastic gradient descent for streaming linear and rectified linear systems with Massart noise. CoRR abs/2403.01204 (2024) - [i20]Michal Derezinski
, Daniel LeJeune, Deanna Needell, Elizaveta Rebrova:
Fine-grained Analysis and Faster Algorithms for Iteratively Solving Linear Systems. CoRR abs/2405.05818 (2024) - [i19]Jackie Lok, Rishi Sonthalia, Elizaveta Rebrova:
Discrete error dynamics of mini-batch gradient descent for least squares regression. CoRR abs/2406.03696 (2024) - [i18]Rishi Sonthalia, Jackie Lok, Elizaveta Rebrova:
On Regularization via Early Stopping for Least Squares Regression. CoRR abs/2406.04425 (2024) - [i17]Abraar Chaudhry, Elizaveta Rebrova:
Learning nonnegative matrix factorizations from compressed data. CoRR abs/2409.04994 (2024) - 2023
- [c7]Jamie Haddock, Anna Ma, Elizaveta Rebrova:
On Subsampled Quantile Randomized Kaczmarz. Allerton 2023: 1-8 - [i16]Elizaveta Rebrova, Palina Salanevich:
On Graph Uncertainty Principle and Eigenvector Delocalization. CoRR abs/2306.15810 (2023) - [i15]Jamie Haddock, Anna Ma, Elizaveta Rebrova:
On Subsampled Quantile Randomized Kaczmarz. CoRR abs/2308.07987 (2023) - [i14]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) - [i13]Jackie Lok, Elizaveta Rebrova:
A subspace constrained randomized Kaczmarz method for structure or external knowledge exploitation. CoRR abs/2309.04889 (2023) - 2022
- [j4]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) - [i12]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) - [i11]Michal Derezinski, Elizaveta Rebrova:
Sharp Analysis of Sketch-and-Project Methods via a Connection to Randomized Singular Value Decomposition. CoRR abs/2208.09585 (2022) - 2021
- [j3]Elizaveta Rebrova, Deanna Needell:
On block Gaussian sketching for the Kaczmarz method. Numer. Algorithms 86(1): 443-473 (2021) - [j2]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) - [c6]Joshua Vendrow, Jamie Haddock, Elizaveta Rebrova, Deanna Needell:
On a Guided Nonnegative Matrix Factorization. ICASSP 2021: 3265-32369 - [i10]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) - [i9]Elizaveta Rebrova, Yu-Hang Tang:
Nonlinear Matrix Approximation with Radial Basis Function Components. CoRR abs/2106.02018 (2021) - [i8]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) - 2020
- [j1]Yang Liu, Wissam M. Sid-Lakhdar, Elizaveta Rebrova, Pieter Ghysels, Xiaoye Sherry Li:
A parallel hierarchical blocked adaptive cross approximation algorithm. Int. J. High Perform. Comput. Appl. 34(4) (2020) - [c5]Jamie Haddock, Deanna Needell, Elizaveta Rebrova, William Swartworth:
Stochastic Gradient Descent Variants for Corrupted Systems of Linear Equations. CISS 2020: 1-6 - [c4]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 - [c3]Gustavo Chávez, Yang Liu, Pieter Ghysels, Xiaoye Sherry Li, Elizaveta Rebrova:
Scalable and Memory-Efficient Kernel Ridge Regression. IPDPS 2020: 956-965 - [i7]Jamie Haddock, Deanna Needell, Elizaveta Rebrova, William Swartworth:
Quantile-based Iterative Methods for Corrupted Systems of Linear Equations. CoRR abs/2009.08089 (2020) - [i6]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) - [i5]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) - [i4]Joshua Vendrow, Jamie Haddock, Elizaveta Rebrova, Deanna Needell:
On a Guided Nonnegative Matrix Factorization. CoRR abs/2010.11365 (2020)
2010 – 2019
- 2019
- [c2]Elizaveta Rebrova, Deanna Needell:
Sketching for Motzkin's Iterative Method for Linear Systems. ACSSC 2019: 271-275 - [i3]Elizaveta Rebrova, Deanna Needell:
Sketching for Motzkin's Iterative Method for Linear Systems. CoRR abs/1912.00771 (2019) - [i2]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
- [c1]Elizaveta Rebrova, Gustavo Chavez, Yang Liu, Pieter Ghysels, Xiaoye Sherry Li:
A Study of Clustering Techniques and Hierarchical Matrix Formats for Kernel Ridge Regression. IPDPS Workshops 2018: 883-892 - [i1]Elizaveta Rebrova, Gustavo Chavez, Yang Liu, Pieter Ghysels, Xiaoye Sherry Li:
A Study of Clustering Techniques and Hierarchical Matrix Formats for Kernel Ridge Regression. CoRR abs/1803.10274 (2018)
Coauthor Index
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last updated on 2024-10-22 21:17 CEST by the dblp team
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