Ethan N. Epperly

32 papers A* 2Journal 30

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Does block size matter in randomized block Krylov low-rank approximation? SODA Tyler Chen, Ethan N. Epperly, Raphael A. Meyer, Christopher Musco, Akash Rao
2026	J	`jnl`	Fast, High-Accuracy, Randomized Nullspace Computations for Tall Matrices. CoRR Ethan N. Epperly, Taejun Park, Yuji Nakatsukasa
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`	Successive randomized compression: A randomized algorithm for the compressed MPO-MPS product. Quantum Chris Camaño, Ethan N. Epperly, Joel A. Tropp
2026	J	`jnl`	The matrix-vector complexity of Ax=b. CoRR Michal Derezinski, Ethan N. Epperly, Raphael A. Meyer
2025	J	`jnl`	Adaptive randomized pivoting and volume sampling. CoRR Ethan N. Epperly
2025	J	`jnl`	Does block size matter in randomized block Krylov low-rank approximation? CoRR Tyler Chen, Ethan N. Epperly, Raphael A. Meyer, Christopher Musco, Akash Rao
2025	J	`jnl`	Embrace Rejection: Kernel Matrix Approximation by Accelerated Randomly Pivoted Cholesky. SIAM J. Matrix Anal. Appl. Ethan N. Epperly, Joel A. Tropp, Robert J. Webber
2025	J	`jnl`	Faster Linear Algebra Algorithms with Structured Random Matrices. CoRR Chris Camaño, Ethan N. Epperly, Raphael A. Meyer, Joel A. Tropp
2025	J	`jnl`	Make the most of what you have: Resource-efficient randomized algorithms for matrix computations. CoRR Ethan N. Epperly
2025	J	`jnl`	Stable algorithms for general linear systems by preconditioning the normal equations. CoRR Ethan N. Epperly, Anne Greenbaum, Yuji Nakatsukasa
2025	J	`jnl`	Successive randomized compression: A randomized algorithm for the compressed MPO-MPS product. CoRR Chris Camaño, Ethan N. Epperly, Joel A. Tropp
2025	J	`jnl`	Superfast Direct Inversion of the Nonuniform Discrete Fourier Transform via Hierarchically Semiseparable Least Squares. SIAM J. Sci. Comput. Heather Wilber, Ethan N. Epperly, Alex H. Barnett
2024	J	`jnl`	A superfast direct inversion method for the nonuniform discrete Fourier transform. CoRR Heather Wilber, Ethan N. Epperly, Alex H. Barnett
2024	J	`jnl`	Efficient Error and Variance Estimation for Randomized Matrix Computations. SIAM J. Sci. Comput. Ethan N. Epperly, Joel A. Tropp
2024	J	`jnl`	Embrace rejection: Kernel matrix approximation by accelerated randomly pivoted Cholesky. CoRR Ethan N. Epperly, Joel A. Tropp, Robert J. Webber
2024	J	`jnl`	Fast and Forward Stable Randomized Algorithms for Linear Least-Squares Problems. SIAM J. Matrix Anal. Appl. Ethan N. Epperly
2024	J	`jnl`	Fast randomized least-squares solvers can be just as accurate and stable as classical direct solvers. CoRR Ethan N. Epperly, Maike Meier, Yuji Nakatsukasa
2024	J	`jnl`	Randomized Kaczmarz with tail averaging. CoRR Ethan N. Epperly, Gil Goldshlager, Robert J. Webber
2024	A*	`conf`	The ESPRIT Algorithm Under High Noise: Optimal Error Scaling and Noisy Super-Resolution. FOCS Zhiyan Ding, Ethan N. Epperly, Lin Lin, Ruizhe Zhang
2024	J	`jnl`	The ESPRIT algorithm under high noise: Optimal error scaling and noisy super-resolution. CoRR Zhiyan Ding, Ethan N. Epperly, Lin Lin, Ruizhe Zhang
2024	J	`jnl`	XTrace: Making the Most of Every Sample in Stochastic Trace Estimation. SIAM J. Matrix Anal. Appl. Ethan N. Epperly, Joel A. Tropp, Robert J. Webber
2023	J	`jnl`	Fast and forward stable randomized algorithms for linear least-squares problems. CoRR Ethan N. Epperly
2023	J	`jnl`	Kernel Quadrature with Randomly Pivoted Cholesky. CoRR Ethan N. Epperly, Elvira Moreno
2023	J	`jnl`	Robust, randomized preconditioning for kernel ridge regression. CoRR Mateo Díaz, Ethan N. Epperly, Zachary Frangella, Joel A. Tropp, Robert J. Webber
2023	J	`jnl`	XTrace: Making the most of every sample in stochastic trace estimation. CoRR Ethan N. Epperly, Joel A. Tropp, Robert J. Webber
2022	J	`jnl`	$(L_r, L_r, 1)$-Decompositions, Sparse Component Analysis, and the Blind Separation of Sums of Exponentials. SIAM J. Matrix Anal. Appl. Nithin Govindarajan, Ethan N. Epperly, Lieven De Lathauwer
2022	J	`jnl`	A Theory of Quantum Subspace Diagonalization. SIAM J. Matrix Anal. Appl. Ethan N. Epperly, Lin Lin, Yuji Nakatsukasa
2022	J	`jnl`	Jackknife Variability Estimation For Randomized Matrix Computations. CoRR Ethan N. Epperly, Joel A. Tropp
2022	J	`jnl`	Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations. CoRR Yifan Chen, Ethan N. Epperly, Joel A. Tropp, Robert J. Webber
2021	J	`jnl`	A Theory of Quantum Subspace Diagonalization. CoRR Ethan N. Epperly, Lin Lin, Yuji Nakatsukasa
2021	J	`jnl`	Minimal Rank Completions for Overlapping Blocks. CoRR Ethan N. Epperly, Nithin Govindarajan, Shivkumar Chandrasekaran