LSMB: Minimizing the Backward Error for Least-Squares Problems. - Eric Hallman; Ming Gu 002 (SIAM J. Matrix Anal. Appl., 2018)

Sharp 2-Norm Error Bounds for LSQR and the Conjugate Gradient Method. - Eric Hallman (SIAM J. Matrix Anal. Appl., 2020)

Faster stochastic trace estimation with a Chebyshev product identity. - Eric Hallman (Appl. Math. Lett., 2021)

A Block Bidiagonalization Method for Fixed-Precision Low-Rank Matrix Approximation. - Eric Hallman (CoRR, 2021)

A Multilevel Approach to Stochastic Trace Estimation. - Eric Hallman; Devon Troester (CoRR, 2021)

A Refined Probabilistic Error Bound for Sums. - Eric Hallman (CoRR, 2021)

Deterministic and Probabilistic Error Bounds for Floating Point Summation Algorithms. - Eric Hallman; Ilse C. F. Ipsen (CoRR, 2021)

A Block Bidiagonalization Method for Fixed-Accuracy Low-Rank Matrix Approximation. - Eric Hallman (SIAM J. Matrix Anal. Appl., 2022)

Randomized Algorithms for Rounding in the Tensor-Train Format. - Hussam Al Daas; Grey Ballard; Paul Cazeaux; Eric Hallman; Agnieszka Miedlar; Mirjeta Pasha; Tim W. Reid; Arvind K. Saibaba (SIAM J. Sci. Comput., 2023)

Monte Carlo Methods for Estimating the Diagonal of a Real Symmetric Matrix. - Eric Hallman; Ilse C. F. Ipsen; Arvind K. Saibaba (SIAM J. Matrix Anal. Appl., 2023)

Krylov-Aware Stochastic Trace Estimation. - Tyler Chen; Eric Hallman (SIAM J. Matrix Anal. Appl., 2023)

Precision-aware deterministic and probabilistic error bounds for floating point summation. - Eric Hallman; Ilse C. F. Ipsen (Numerische Mathematik, 2023)

Extremal bounds for Gaussian trace estimation. - Eric Hallman (CoRR, 2024)