John Urschel

Orcid: 0000-0002-5401-821X

Affiliations:
  • Massachusetts Institute of Technology (MIT), Department of Mathematics, Cambridge, MA, USA (PhD 2021)
  • Harvard University, Society of Fellows, Cambridge, MA, USA
  • Institute for Advanced Study (IAS), School of Mathematics, Princeton, NJ, USA (former)


According to our database1, John Urschel authored at least 18 papers between 2017 and 2026.

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Timeline

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Bibliography

2026
Spectral density estimation for normal matrices.
CoRR, May, 2026

On the exponential rate of the condition number of Fourier submatrices and Vandermonde matrices.
CoRR, April, 2026

The largest 5th pivot may be the root of a 61st degree polynomial.
CoRR, February, 2026

2025
Estimating the Matrix <i>p → q</i> Norm.
SIAM J. Matrix Anal. Appl., 2025

2024
Some New Results on the Maximum Growth Factor in Gaussian Elimination.
SIAM J. Matrix Anal. Appl., 2024

Estimating the numerical range with a Krylov subspace.
CoRR, 2024

On a perturbation analysis of Higham squared maximum Gaussian elimination growth matrices.
CoRR, 2024

Hamilton Powers of Eulerian Digraphs.
Electron. J. Comb., 2024

2023
A New Upper Bound For the Growth Factor in Gaussian Elimination with Complete Pivoting.
CoRR, 2023

Estimating the matrix p → q norm.
CoRR, 2023

Representing the Special Linear Group with Block Unitriangular Matrices.
CoRR, 2023

2021
Uniform Error Estimates for the Lanczos Method.
SIAM J. Matrix Anal. Appl., 2021

Testing gap <i>k</i>-planarity is NP-complete.
Inf. Process. Lett., 2021

Regarding Two Conjectures on Clique and Biclique Partitions.
Electron. J. Comb., 2021

Multidimensional Scaling: Approximation and Complexity.
Proceedings of the 38th International Conference on Machine Learning, 2021

2017
On The Characterization and Uniqueness of Centroidal Voronoi Tessellations.
SIAM J. Numer. Anal., 2017

Learning Determinantal Point Processes with Moments and Cycles.
Proceedings of the 34th International Conference on Machine Learning, 2017

Rates of estimation for determinantal point processes.
Proceedings of the 30th Conference on Learning Theory, 2017


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