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We consider the computation of the matrix logarithm by using numerical quadrature. The efficiency of numerical quadrature depends on the integrand and the choice of quadrature formula. The Gauss--Legendre quadrature has been conventionally…

Numerical Analysis · Mathematics 2019-09-09 Fuminori Tatsuoka , Tomohiro Sogabe , Yuto Miyatake , Shao-Liang Zhang

In this paper, we consider the problem of Gaussian approximation for the online linear regression task. We derive the corresponding rates for the setting of a constant learning rate and study the explicit dependence of the convergence rate…

Machine Learning · Statistics 2025-09-18 Marat Khusainov , Marina Sheshukova , Alain Durmus , Sergey Samsonov

In studying the complexity of iterative processes it is usually assumed that the arithmetic operations of addition, multiplication, and division can be performed in certain constant times. This assumption is invalid if the precision…

Computational Complexity · Computer Science 2021-03-22 Richard P. Brent

The multiplication of matrices is an important arithmetic operation in computational mathematics. In the context of hierarchical matrices, this operation can be realized by the multiplication of structured block-wise low-rank matrices,…

Numerical Analysis · Mathematics 2018-05-24 Jürgen Dölz , Helmut Harbrecht , Michael D. Multerer

The paper presents a comparative analysis of iterative numerical methods of Jacobi and Gauss-Seidel for solving systems of linear algebraic equations (SLAEs) with complex and real matrices. The ranges of convergence for both methods for…

Numerical Analysis · Mathematics 2024-02-19 Pavel Khrapov , Nikita Volkov

Estimating longitudinal treatment effects is essential for sequential decision-making but is challenging due to treatment-confounder feedback. While Iterative Conditional Expectation (ICE) G-computation offers a principled approach, its…

Machine Learning · Computer Science 2026-02-16 Wenxin Chen , Weishen Pan , Kyra Gan , Fei Wang

Estimation of the precision matrix (or inverse covariance matrix) is of great importance in statistical data analysis and machine learning. However, as the number of parameters scales quadratically with the dimension $p$, computation…

Computation · Statistics 2022-11-02 Qian LI , Binyan Jiang , Defeng Sun

We define a new cost model for the call-by-value lambda-calculus satisfying the invariance thesis. That is, under the proposed cost model, Turing machines and the call-by-value lambda-calculus can simulate each other within a polynomial…

Logic in Computer Science · Computer Science 2007-05-23 Ugo Dal Lago , Simone Martini

This paper investigates the iterates $\hbb^1,\dots,\hbb^T$ obtained from iterative algorithms in high-dimensional linear regression problems, in the regime where the feature dimension $p$ is comparable with the sample size $n$, i.e., $p…

Machine Learning · Statistics 2024-04-30 Pierre C. Bellec , Kai Tan

On modern parallel architectures, the cost of synchronization among processors can often dominate the cost of floating-point computation. Several modifications of the existing methods have been proposed in order to keep the communication…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-12-10 Qinmeng Zou , Frederic Magoules

We consider evolutionary systems, i.e. systems of linear partial differential equations arising from the mathematical physics. For these systems there exists a general solution theory in exponentially weighted spaces which can be exploited…

Numerical Analysis · Mathematics 2023-04-26 Sebastian Franz

In this paper, we discuss numerical methods for the eigenvalue decomposition of real symmetric matrices. While many existing methods can compute approximate eigenpairs with sufficiently small backward errors, the magnitude of the resulting…

Numerical Analysis · Mathematics 2026-02-24 Takeshi Terao , Katsuhisa Ozaki

The efficient parallel execution of complex computations requires balancing the workload across processors while minimizing the communication between them. This inherent trade-off is often captured by graph partitioning or DAG scheduling…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-04 Pál András Papp , Toni Böhnlein , A. N. Yzelman

Signal inference problems with non-Gaussian posteriors can be hard to tackle. Through using the concept of Gibbs free energy these posteriors are rephrased as Gaussian posteriors for the price of computing various expectation values with…

Methodology · Statistics 2016-11-18 Reimar H. Leike , Torsten A. Enßlin

A fundamental problem arising in many applications in Web science and social network analysis is, given an arbitrary approximation factor $c>1$, to output a set $S$ of nodes that with high probability contains all nodes of PageRank at least…

Data Structures and Algorithms · Computer Science 2015-03-20 Christian Borgs , Michael Brautbar , Jennifer Chayes , Shang-Hua Teng

We study an inexact inner-outer generalized Golub-Kahan algorithm for the solution of saddle-point problems with a two-times-two block structure. In each outer iteration, an inner system has to be solved which in theory has to be done…

Numerical Analysis · Mathematics 2024-05-15 Vincent Darrigrand , Andrei Dumitrasc , Carola Kruse , Ulrich Ruede

We analyze the bit complexity of efficient algorithms for fundamental optimization problems, such as linear regression, $p$-norm regression, and linear programming (LP). State-of-the-art algorithms are iterative, and in terms of the number…

Data Structures and Algorithms · Computer Science 2023-04-06 Mehrdad Ghadiri , Richard Peng , Santosh S. Vempala

We review the method of the calculation of multiloop integrals recently suggested in Ref.[Lee2010]. A simple method of derivation of the dimensional recurrence relation suitable for automatization is given. Some new analytic results are…

High Energy Physics - Phenomenology · Physics 2010-12-13 R. N. Lee

This work is to popularize the method of computing the distribution of the excursion times for a Gaussian process that involves extended and multivariate Rice's formula. The approach was used in numerical implementations of the…

Probability · Mathematics 2020-07-29 Georg Lindgren , Krzysztof Podgorski , Igor Rychlik

In this article we investigate a finite element formulation of strongly monotone quasi-linear elliptic PDEs in the context of fixed-point iterations. As opposed to Newton's method, which requires information from the previous iteration in…

Numerical Analysis · Mathematics 2015-07-01 Scott Congreve , Thomas P. Wihler