Fast randomized iteration: diffusion Monte Carlo through the lens of numerical linear algebra [PDF]
, 2017 We review the basic outline of the highly successful diffusion Monte Carlo technique commonly used in contexts ranging from electronic structure calculations to rare event simulation and data assimilation, and propose a new class of randomized iterative ...
Lim, Lek-Heng, Weare, Jonathan
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Fast computation of the eigensystem of genomic similarity matrices [PDF]
BMC BioinformaticsThe computation of a similarity measure for genomic data is a standard tool in computational genetics. The principal components of such matrices are routinely used to correct for biases due to confounding by population stratification, for instance in ...
Georg Hahn +7 more
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Lectures on Randomized Numerical Linear Algebra [PDF]
, 2017 This chapter is based on lectures on Randomized Numerical Linear Algebra from the 2016 Park City Mathematics Institute summer school on The Mathematics of Data.Comment: To appear in the edited volume of lectures from the 2016 PCMI summer ...
Drineas, Petros, Mahoney, Michael W.
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Approximating Hamiltonian dynamics with the Nyström method [PDF]
Quantum, 2020 Simulating the time-evolution of quantum mechanical systems is BQP-hard and expected to be one of the foremost applications of quantum computers. We consider classical algorithms for the approximation of Hamiltonian dynamics using subsampling methods ...
Alessandro Rudi +5 more
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Constructing Compact Signatures for Individual Fingerprinting of Brain Connectomes
Frontiers in Neuroscience, 2021 Recent neuroimaging studies have shown that functional connectomes are unique to individuals, i.e., two distinct fMRIs taken over different sessions of the same subject are more similar in terms of their connectomes than those from two different subjects.
Vikram Ravindra +2 more
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Efficient Asynchronous Semi-Stochastic Block Coordinate Descent Methods for Large-Scale SVD
IEEE Access, 2021 Eigenvector computation such as Singular Value Decomposition (SVD) is one of the most fundamental problems in machine learning, optimization and numerical linear algebra.
Fanhua Shang +4 more
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Efficient Forced Response Computations of Acoustical Systems with a State-Space Approach
Acoustics, 2021 State-space models have been successfully employed for model order reduction and control purposes in acoustics in the past. However, due to the cubic complexity of the singular value decomposition, which makes up the core of many subspace system ...
Art J. R. Pelling, Ennes Sarradj
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Scalable diagnostics for global atmospheric chemistry using Ristretto library (version 1.0) [PDF]
Geoscientific Model Development, 2019 We introduce a new set of algorithmic tools capable of producing scalable, low-rank decompositions of global spatiotemporal atmospheric chemistry data.
M. Velegar +4 more
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Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions [PDF]
, 2010 Low-rank matrix approximations, such as the truncated singular value decomposition and the rank-revealing QR decomposition, play a central role in data analysis and scientific computing.
Halko, Nathan +2 more
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Random Sampling in Computational Algebra: Helly Numbers and Violator Spaces [PDF]
, 2015 This paper transfers a randomized algorithm, originally used in geometric optimization, to computational problems in commutative algebra. We show that Clarkson's sampling algorithm can be applied to two problems in computational algebra: solving large ...
De Loera, Jesús A. +2 more
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