1 citations · 1 across the 3 of their papers we have counts for
5 papers
Error bounds for the Sherman-Morrison formula and its modification with improved stability
Behnam Hashemi, Yuji Nakatsukasa
It is known that the Sherman--Morrison (SM) formula is not numerically stable. In recent work, we introduced SMIR, an algorithm that incorporates iterative refinement to enhance th…
Instability of the Sherman-Morrison formula and stabilization by iterative refinement
Behnam Hashemi, Yuji Nakatsukasa
Owing to its simplicity and efficiency, the Sherman-Morrison (SM) formula has seen widespread use across various scientific and engineering applications for solving rank-one pertur…
LREI: A fast numerical solver for quantum Landau-Lifshitz equations
Davoud Mirzaei, Behnam Hashemi, Vahid Azimi-Mousolou
We develop LREI (Low-Rank Eigenmode Integration), a memory- and time-efficient scheme for solving quantum Landau-Lifshitz (q-LL) and quantum Landau-Lifshitz-Gilbert (q-LLG) equatio…
A sequential multilinear Nyström algorithm for streaming low-rank approximation of tensors in Tucker format
Alberto Bucci, Behnam Hashemi
We present a sequential version of the multilinear Nyström algorithm which is suitable for the low-rank Tucker approximation of tensors given in a streaming format. Accessing the t…
RTSMS: Randomized Tucker with single-mode sketching
Behnam Hashemi, Yuji Nakatsukasa
We propose RTSMS (Randomized Tucker via Single-Mode-Sketching), a randomized algorithm for approximately computing a low-rank Tucker decomposition of a given tensor. It uses sketch…