Randomized Orthogonalization and Krylov Subspace Methods: Principles and Algorithms

Lecture notes in computational science and engineering 2026 Book chapter Open access

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Authors: Jean-Guillaume de Damas, Laura Grigori, Igor Simunec, Edouard Timsit

DOI: 10.1007/978-3-032-33428-2_6

Cited by: 0

References: 65

Fields of Study & Subjects

Matrix Theory and Algorithms Stochastic Gradient Optimization Techniques Polynomial and algebraic computation

References 65