Raphael A. Meyer

According to our database, Raphael A. Meyer authored at least 19 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Quantifying Epistemic Uncertainty in Diffusion Models.

Aditi Gupta, Raphael A. Meyer, Yotam Yaniv, Elynn Chen, N. Benjamin Erichson

CoRR, February, 2026

Linear Systems and Eigenvalue Problems: Open Questions from a Simons Workshop.

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

CoRR, February, 2026

The matrix-vector complexity of Ax=b.

Michal Derezinski, Ethan N. Epperly, Raphael A. Meyer

CoRR, February, 2026

Hutchinson's Estimator is Bad at Kronecker-Trace-Estimation.

Raphael A. Meyer, Haim Avron

SIAM J. Matrix Anal. Appl., 2026

Debiasing Polynomial and Fourier Regression.

Chris Camaño, Raphael A. Meyer, Kevin Shu

Proceedings of the 2026 Symposium on Simplicity in Algorithms, 2026

Does block size matter in randomized block Krylov low-rank approximation?

Tyler Chen, Ethan N. Epperly, Raphael A. Meyer, Christopher Musco, Akash Rao

Proceedings of the 2026 Annual ACM-SIAM Symposium on Discrete Algorithms, 2026

2025

Faster Linear Algebra Algorithms with Structured Random Matrices.

Chris Camaño, Ethan N. Epperly, Raphael A. Meyer, Joel A. Tropp

CoRR, August, 2025

Algorithm-Agnostic Low-Rank Approximation of Operator Monotone Matrix Functions.

David Persson, Raphael A. Meyer, Christopher Musco

SIAM J. Matrix Anal. Appl., 2025

Understanding the Kronecker Matrix-Vector Complexity of Linear Algebra.

Raphael A. Meyer, William J. Swartworth, David P. Woodruff

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

On the Unreasonable Effectiveness of Single Vector Krylov Methods for Low-Rank Approximation.

Raphael A. Meyer, Cameron Musco, Christopher Musco

Proceedings of the 2024 ACM-SIAM Symposium on Discrete Algorithms, 2024

2023

Near-Linear Sample Complexity for <i>L_p</i> Polynomial Regression.

Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou

Proceedings of the 2023 ACM-SIAM Symposium on Discrete Algorithms, 2023

2022

Near-Linear Sample Complexity for L_p Polynomial Regression.

Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou

CoRR, 2022

Fast Regression for Structured Inputs.

Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Hutch++: Optimal Stochastic Trace Estimation.

Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff

Proceedings of the 4th Symposium on Simplicity in Algorithms, 2021

2020

The Statistical Cost of Robust Kernel Hyperparameter Tuning.

Raphael A. Meyer, Christopher Musco

CoRR, 2020

The Statistical Cost of Robust Kernel Hyperparameter Turning.

Raphael A. Meyer, Christopher Musco

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

On the Statistical Efficiency of Optimal Kernel Sum Classifiers.

Raphael Arkady Meyer, Jean Honorio

CoRR, 2019

Optimality Implies Kernel Sum Classifiers are Statistically Efficient.

Raphael A. Meyer, Jean Honorio

Proceedings of the 36th International Conference on Machine Learning, 2019

2017

Characterizing optimal security and round-complexity for secure OR evaluation.

Amisha Jhanji, Hemanta K. Maji, Raphael Arkady Meyer

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017