Elizaveta Rebrova

47 papers A 1B 1Misc 3Journal 39Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Fast and low-memory compressive sensing algorithms for low tucker-rank tensor approximation from streamed measurements. Numer. Algorithms Cullen Haselby, Mark A. Iwen, Deanna Needell, Elizaveta Rebrova, William Swartworth
2026	J	`jnl`	Linear Systems and Eigenvalue Problems: Open Questions from a Simons Workshop. CoRR Noah Amsel, Yves Baumann, Paul Beckman, Peter Bürgisser, Chris Camaño, Tyler Chen, Edmond Chow, Anil Damle, Michal Derezinski, Mark Embree, Ethan N. Epperly, Robert D. Falgout, Mark Fornace, Anne Greenbaum, Chen Greif, Diana Halikias, Zhen Huang, Elias Jarlebring, Yiannis Koutis, Daniel Kressner, Rasmus Kyng, Jörg Liesen, Jackie Lok, Raphael A. Meyer, Yuji Nakatsukasa, Kate Pearce, Richard Peng, David Persson, Elizaveta Rebrova, Ryan Schneider, Rikhav Shah, Edgar Solomonik, Nikhil Srivastava, Alex Townsend, Robert J. Webber, Jess Williams
2026	J	`jnl`	Quantile Randomized Kaczmarz Algorithm with Whitelist Trust Mechanism. CoRR Sofiia Shvaiko, Longxiu Huang, Elizaveta Rebrova
2025	J	`jnl`	Beyond Expectation: Concentration Inequalities for Randomized Iterative Methods. CoRR Toby Anderson, Max Collins, Jamie Haddock, Jackie Lok, Elizaveta Rebrova
2025	J	`jnl`	Data-Driven, ML-assisted Approaches to Problem Well-Posedness. CoRR Tom Bertalan, George A. Kevrekidis, Eleni D. Koronaki, Siddhartha Mishra, Elizaveta Rebrova, Yannis G. Kevrekidis
2025	B	`conf`	Error dynamics of mini-batch gradient descent with random reshuffling for least squares regression. ALT Jackie Lok, Rishi Sonthalia, Elizaveta Rebrova
2025	J	`jnl`	Fine-grained Analysis and Faster Algorithms for Iteratively Solving Linear Systems. J. Mach. Learn. Res. Michal Derezinski, Daniel LeJeune, Deanna Needell, Elizaveta Rebrova
2025	J	`jnl`	On Trimming Tensor-structured Measurements and Efficient Low-rank Tensor Recovery. CoRR Shambhavi Suryanarayanan, Elizaveta Rebrova
2025	J	`jnl`	Randomized Kaczmarz Methods with Beyond-Krylov Convergence. CoRR Michal Derezinski, Deanna Needell, Elizaveta Rebrova, Jiaming Yang
2025	J	`jnl`	Randomized Kaczmarz Methods with Beyond-Krylov Convergence. SIAM J. Matrix Anal. Appl. Michal Derezinski, Deanna Needell, Elizaveta Rebrova, Jiaming Yang
2025	J	`jnl`	Scientific Applications Leveraging Randomized Linear Algebra. CoRR Vivak Patel, Daniel Adrian Maldonado, Maksim Melnichenko, Nathaniel Pritchard, Vishwas Rao, Elizaveta Rebrova, Sriram Sankararaman
2025	J	`jnl`	Stochastic Gradient Descent for Streaming Linear and Rectified Linear Systems with Adversarial Corruptions. SIAM J. Math. Data Sci. Halyun Jeong, Deanna Needell, Elizaveta Rebrova
2025	J	`jnl`	Subspace-constrained randomized coordinate descent for linear systems with good low-rank matrix approximations. CoRR Jackie Lok, Elizaveta Rebrova
2024	J	`jnl`	Discrete error dynamics of mini-batch gradient descent for least squares regression. CoRR Jackie Lok, Rishi Sonthalia, Elizaveta Rebrova
2024	J	`jnl`	Fine-grained Analysis and Faster Algorithms for Iteratively Solving Linear Systems. CoRR Michal Derezinski, Daniel LeJeune, Deanna Needell, Elizaveta Rebrova
2024	J	`jnl`	Learning nonnegative matrix factorizations from compressed data. CoRR Abraar Chaudhry, Elizaveta Rebrova
2024	J	`jnl`	On Regularization via Early Stopping for Least Squares Regression. CoRR Rishi Sonthalia, Jackie Lok, Elizaveta Rebrova
2024	J	`jnl`	Sharp Analysis of Sketch-and-Project Methods via a Connection to Randomized Singular Value Decomposition. SIAM J. Math. Data Sci. Michal Derezinski, Elizaveta Rebrova
2024	J	`jnl`	Sparseness-constrained nonnegative tensor factorization for detecting topics at different time scales. Frontiers Appl. Math. Stat. Lara Kassab, Alona Kryshchenko, Hanbaek Lyu, Denali Molitor, Deanna Needell, Elizaveta Rebrova, Jiahong Yuan
2024	J	`jnl`	Stochastic gradient descent for streaming linear and rectified linear systems with Massart noise. CoRR Halyun Jeong, Deanna Needell, Elizaveta Rebrova
2023	J	`jnl`	A subspace constrained randomized Kaczmarz method for structure or external knowledge exploitation. CoRR Jackie Lok, Elizaveta Rebrova
2023	J	`jnl`	Fast and Low-Memory Compressive Sensing Algorithms for Low Tucker-Rank Tensor Approximation from Streamed Measurements. CoRR Cullen Haselby, Mark A. Iwen, Deanna Needell, Elizaveta Rebrova, William Swartworth
2023	J	`jnl`	On Graph Uncertainty Principle and Eigenvector Delocalization. CoRR Elizaveta Rebrova, Palina Salanevich
2023	—	`conf`	On Subsampled Quantile Randomized Kaczmarz. Allerton Jamie Haddock, Anna Ma, Elizaveta Rebrova
2023	J	`jnl`	On Subsampled Quantile Randomized Kaczmarz. CoRR Jamie Haddock, Anna Ma, Elizaveta Rebrova
2022	J	`jnl`	On Block Accelerations of Quantile Randomized Kaczmarz for Corrupted Systems of Linear Equations. CoRR Lu Cheng, Benjamin Jarman, Deanna Needell, Elizaveta Rebrova
2022	J	`jnl`	Quantile-Based Iterative Methods for Corrupted Systems of Linear Equations. SIAM J. Matrix Anal. Appl. Jamie Haddock, Deanna Needell, Elizaveta Rebrova, William Swartworth
2022	J	`jnl`	Sharp Analysis of Sketch-and-Project Methods via a Connection to Randomized Singular Value Decomposition. CoRR Michal Derezinski, Elizaveta Rebrova
2021	J	`jnl`	Analysis of Legal Documents via Non-negative Matrix Factorization Methods. CoRR Ryan Budahazy, Lu Cheng, Yihuan Huang, Andrew Johnson, Pengyu Li, Joshua Vendrow, Zhoutong Wu, Denali Molitor, Elizaveta Rebrova, Deanna Needell
2021	J	`jnl`	Lower Memory Oblivious (Tensor) Subspace Embeddings with Fewer Random Bits: Modewise Methods for Least Squares. SIAM J. Matrix Anal. Appl. Mark A. Iwen, Deanna Needell, Elizaveta Rebrova, Ali Zare
2021	J	`jnl`	Modewise Operators, the Tensor Restricted Isometry Property, and Low-Rank Tensor Recovery. CoRR Mark A. Iwen, Deanna Needell, Michael Perlmutter, Elizaveta Rebrova
2021	J	`jnl`	Nonlinear Matrix Approximation with Radial Basis Function Components. CoRR Elizaveta Rebrova, Yu-Hang Tang
2021	Misc	`conf`	On a Guided Nonnegative Matrix Factorization. ICASSP Joshua Vendrow, Jamie Haddock, Elizaveta Rebrova, Deanna Needell
2021	J	`jnl`	On block Gaussian sketching for the Kaczmarz method. Numer. Algorithms Elizaveta Rebrova, Deanna Needell
2020	J	`jnl`	A parallel hierarchical blocked adaptive cross approximation algorithm. Int. J. High Perform. Comput. Appl. Yang Liu, Wissam M. Sid-Lakhdar, Elizaveta Rebrova, Pieter Ghysels, Xiaoye Sherry Li
2020	—	`conf`	COVID-19 Literature Topic-Based Search via Hierarchical NMF. NLP4COVID@EMNLP Rachel Grotheer, Longxiu Huang, Yihuan Huang, Alona Kryshchenko, Oleksandr Kryshchenko, Pengyu Li, Xia Li, Elizaveta Rebrova, Kyung Ha, Deanna Needell
2020	J	`jnl`	COVID-19 Literature Topic-Based Search via Hierarchical NMF. CoRR Rachel Grotheer, Yihuan Huang, Pengyu Li, Elizaveta Rebrova, Deanna Needell, Longxiu Huang, Alona Kryshchenko, Xia Li, Kyung Ha, Oleksandr Kryshchenko
2020	J	`jnl`	On Nonnegative Matrix and Tensor Decompositions for COVID-19 Twitter Dynamics. CoRR Lara Kassab, Alona Kryshchenko, Hanbaek Lyu, Denali Molitor, Deanna Needell, Elizaveta Rebrova
2020	J	`jnl`	On a Guided Nonnegative Matrix Factorization. CoRR Joshua Vendrow, Jamie Haddock, Elizaveta Rebrova, Deanna Needell
2020	J	`jnl`	Quantile-based Iterative Methods for Corrupted Systems of Linear Equations. CoRR Jamie Haddock, Deanna Needell, Elizaveta Rebrova, William Swartworth
2020	A	`conf`	Scalable and Memory-Efficient Kernel Ridge Regression. IPDPS Gustavo Chávez, Yang Liu, Pieter Ghysels, Xiaoye Sherry Li, Elizaveta Rebrova
2020	Misc	`conf`	Stochastic Gradient Descent Variants for Corrupted Systems of Linear Equations. CISS Jamie Haddock, Deanna Needell, Elizaveta Rebrova, William Swartworth
2019	J	`jnl`	Lower Memory Oblivious (Tensor) Subspace Embeddings with Fewer Random Bits: Modewise Methods for Least Squares. CoRR Mark A. Iwen, Deanna Needell, Elizaveta Rebrova, Ali Zare
2019	Misc	`conf`	Sketching for Motzkin's Iterative Method for Linear Systems. ACSSC Elizaveta Rebrova, Deanna Needell
2019	J	`jnl`	Sketching for Motzkin's Iterative Method for Linear Systems. CoRR Elizaveta Rebrova, Deanna Needell
2018	—	`conf`	A Study of Clustering Techniques and Hierarchical Matrix Formats for Kernel Ridge Regression. IPDPS Workshops Elizaveta Rebrova, Gustavo Chavez, Yang Liu, Pieter Ghysels, Xiaoye Sherry Li
2018	J	`jnl`	A Study of Clustering Techniques and Hierarchical Matrix Formats for Kernel Ridge Regression. CoRR Elizaveta Rebrova, Gustavo Chavez, Yang Liu, Pieter Ghysels, Xiaoye Sherry Li