Tyler Chen

According to our database, Tyler Chen authored at least 36 papers between 2019 and 2026.

Collaborative distances:

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

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

Fixed-Sparsity Matrix Approximation from Matrix-Vector Products.

Noah Amsel, Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco

SIAM J. Matrix Anal. Appl., 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

Optimal polynomial approximation to rational matrix functions using the Arnoldi algorithm.

Tyler Chen, Anne Greenbaum, Natalie Wellen

Numer. Algorithms, December, 2025

A simple analysis of a quantum-inspired algorithm for solving low-rank linear systems.

Tyler Chen, Junhyung Lyle Kim, Archan Ray, Shouvanik Chakrabarti, Dylan Herman, Niraj Kumar

CoRR, August, 2025

Query Efficient Structured Matrix Learning.

Noah Amsel, Pratyush Avi, Tyler Chen, Feyza Duman Keles, Chinmay Hegde, Cameron Musco, Christopher Musco, David Persson

CoRR, July, 2025

A Unified Framework for Provably Efficient Algorithms to Estimate Shapley Values.

Tyler Chen, Akshay Seshadri, Mattia J. Villani, Pradeep Niroula, Shouvanik Chakrabarti, Archan Ray, Pranav Deshpande, Romina Yalovetzky, Marco Pistoia, Niraj Kumar

CoRR, June, 2025

GPU-Parallelizable Randomized Sketch-and-Precondition for Linear Regression using Sparse Sign Sketches.

Tyler Chen, Pradeep Niroula, Archan Ray, Pragna Subrahmanya, Marco Pistoia, Niraj Kumar

CoRR, June, 2025

Quasi-optimal hierarchically semi-separable matrix approximation.

Noah Amsel, Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco, David Persson

CoRR, May, 2025

Provably faster randomized and quantum algorithms for k-means clustering via uniform sampling.

Tyler Chen, Archan Ray, Akshay Seshadri, Dylan Herman, Bao Bach, Pranav Deshpande, Abhishek Som, Niraj Kumar, Marco Pistoia

CoRR, April, 2025

A posteriori error bounds for the block-Lanczos method for matrix function approximation.

Qichen Xu, Tyler Chen

Numer. Algorithms, February, 2025

Randomized block-Krylov subspace methods for low-rank approximation of matrix functions.

David Persson, Tyler Chen, Christopher Musco

CoRR, February, 2025

Preconditioning without a preconditioner: faster ridge-regression and Gaussian sampling with randomized block Krylov subspace methods.

Tyler Chen, Caroline Huber, Ethan Lin, Hajar Zaid

CoRR, January, 2025

Randomized Matrix-Free Quadrature: Unified and Uniform Bounds for Stochastic Lanczos Quadrature and the Kernel Polynomial Method.

Tyler Chen, Thomas Trogdon, Shashanka Ubaru

SIAM J. Sci. Comput., 2025

Near-optimal hierarchical matrix approximation from matrix-vector products.

Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco, David Persson

Proceedings of the 2025 Annual ACM-SIAM Symposium on Discrete Algorithms, 2025

Revisiting the Link Accessibility Problem in Scholarly Papers with PLoS ONE Papers.

Tyler Chen, Jian Wu

Proceedings of the ACM/IEEE Joint Conference on Digital Libraries, 2025

2024

Faster Randomized Partial Trace Estimation.

Tyler Chen, Robert Chen, Kevin Li, Skai Nzeuton, Yilu Pan, Yixin Wang

SIAM J. Sci. Comput., 2024

GMRES, pseudospectra, and Crouzeix's conjecture for shifted and scaled Ginibre matrices.

Tyler Chen, Anne Greenbaum, Thomas Trogdon

Math. Comput., 2024

The Lanczos algorithm for matrix functions: a handbook for scientists.

Tyler Chen

CoRR, 2024

Near-optimal convergence of the full orthogonalization method.

Tyler Chen, Gérard Meurant

CoRR, 2024

Large-scale Outdoor Cell-free mMIMO Channel Measurement in an Urban Scenario at 3.5 GHz.

Yuning Zhang, Thomas Choi, Zihang Cheng, Issei Kanno, Masaaki Ito, Jorge Gomez-Ponce, Hussein Hammoud, Bowei Wu, Ashwani Pradhan, Kelvin Arana, Pramod Krishna, Tianyi Yang, Tyler Chen, Ishita Vasishtha, Haoyu Xie, Linyu Sun, Andreas F. Molisch

Proceedings of the 100th IEEE Vehicular Technology Conference, 2024

Nearly Optimal Approximation of Matrix Functions by the Lanczos Method.

Noah Amsel, Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Krylov-Aware Stochastic Trace Estimation.

Tyler Chen, Eric Hallman

SIAM J. Matrix Anal. Appl., September, 2023

Low-Memory Krylov Subspace Methods for Optimal Rational Matrix Function Approximation.

Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco

SIAM J. Matrix Anal. Appl., June, 2023

A spectrum adaptive kernel polynomial method.

Tyler Chen

CoRR, 2023

Near-Optimality Guarantees for Approximating Rational Matrix Functions by the Lanczos Method.

Noah Amsel, Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco

CoRR, 2023

Stability of the Lanczos algorithm on matrices with regular spectral distributions.

Tyler Chen, Thomas Trogdon

CoRR, 2023

2022

Error Bounds for Lanczos-Based Matrix Function Approximation.

Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco

SIAM J. Matrix Anal. Appl., 2022

On the fast convergence of minibatch heavy ball momentum.

Raghu Bollapragada, Tyler Chen, Rachel A. Ward

CoRR, 2022

Numerical computation of the equilibrium-reduced density matrix for strongly coupled open quantum systems.

Tyler Chen, Yu-Chen Cheng

CoRR, 2022

Randomized matrix-free quadrature for spectrum and spectral sum approximation.

Tyler Chen, Thomas Trogdon, Shashanka Ubaru

CoRR, 2022

2021

On the Convergence Rate of Variants of the Conjugate Gradient Algorithm in Finite Precision Arithmetic.

Anne Greenbaum, Hexuan Liu, Tyler Chen

SIAM J. Sci. Comput., 2021

Analysis of stochastic Lanczos quadrature for spectrum approximation.

Tyler Chen, Thomas Trogdon, Shashanka Ubaru

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Predict-and-Recompute Conjugate Gradient Variants.

Tyler Chen, Erin Carson

SIAM J. Sci. Comput., 2020

Rounding random variables to finite precision.

Tyler Chen

CoRR, 2020

2019

Predict-and-recompute conjugate gradient variants.

Tyler Chen

CoRR, 2019