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Presented with a new machine with a specific interconnect topology, algorithm designers use intuition about the symmetry of the algorithm to design time and communication-efficient schedules that map the algorithm to the machine. Is there a…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-12-10 Harsha Vardhan Simhadri

In this paper we introduce a general framework for casting fully dynamic transitive closure into the problem of reevaluating polynomials over matrices. With this technique, we improve the best known bounds for fully dynamic transitive…

Data Structures and Algorithms · Computer Science 2007-05-23 Camil Demetrescu , Giuseppe F. Italiano

In this paper, we present an improved algorithm for the All Pairs Non-decreasing Paths (APNP) problem on weighted simple digraphs, which has running time $\tilde{O}(n^{\frac{3 + \omega}{2}}) = \tilde{O}(n^{2.686})$. Here $n$ is the number…

Data Structures and Algorithms · Computer Science 2019-04-25 Ran Duan , Ce Jin , Hongxun Wu

MDS matrices play a critical role in the design of diffusion layers for block ciphers and hash functions due to their optimal branch number. Involutory and orthogonal MDS matrices offer additional benefits by allowing identical or nearly…

Cryptography and Security · Computer Science 2026-01-23 Yogesh Kumar , Susanta Samanta , Atul Gaur

After Strassen presented the first sub-cubic matrix multiplication algorithm, many Strassen-like algorithms are presented. Most of them with low asymptotic cost have large hidden leading coefficient which are thus impractical. To reduce the…

Symbolic Computation · Computer Science 2022-03-31 Pu Wu , Huiqing Jiang , Zehui Shao , Jin Xu

The sorting operation is one of the most commonly used building blocks in computer programming. In machine learning, it is often used for robust statistics. However, seen as a function, it is piecewise linear and as a result includes many…

Machine Learning · Statistics 2020-07-01 Mathieu Blondel , Olivier Teboul , Quentin Berthet , Josip Djolonga

Despite their tremendous success and versatility, Deep Neural Networks (DNNs) such as Large Language Models (LLMs) suffer from inference inefficiency and rely on advanced computational infrastructure. To address these challenges and make…

Machine Learning · Computer Science 2025-05-05 Mohsen Dehghankar , Mahdi Erfanian , Abolfazl Asudeh

This paper considers fast algorithms for operations on linearized polynomials. We propose a new multiplication algorithm for skew polynomials (a generalization of linearized polynomials) which has sub-quadratic complexity in the polynomial…

Symbolic Computation · Computer Science 2017-07-12 Sven Puchinger , Antonia Wachter-Zeh

We estimate the Boolean complexity of multiplication of structured matrices by a vector and the solution of nonsingular linear systems of equations with these matrices. We study four basic most popular classes, that is, Toeplitz, Hankel,…

Symbolic Computation · Computer Science 2014-04-21 Victor Y. Pan , Elias Tsigaridas

The efficiency of Gr\"obner basis computation, the standard engine for solving systems of polynomial equations, depends on the choice of monomial ordering. Despite a near-continuum of possible monomial orders, most implementations rely on…

Symbolic Computation · Computer Science 2026-02-04 R. Caleb Bunch , Alperen A. Ergür , Melika Golestani , Jessie Tong , Malia Walewski , Yunus E. Zeytuncu

We present new algorithms to detect and correct errors in the lower-upper factorization of a matrix, or the triangular linear system solution, over an arbitrary field. Our main algorithms do not require any additional information or…

Symbolic Computation · Computer Science 2019-01-31 Jean-Guillaume Dumas , Joris Van Der Hoeven , Clément Pernet , Daniel Roche

Linear neural network layers that are either equivariant or invariant to permutations of their inputs form core building blocks of modern deep learning architectures. Examples include the layers of DeepSets, as well as linear layers…

Machine Learning · Computer Science 2023-03-14 Charles Godfrey , Michael G. Rawson , Davis Brown , Henry Kvinge

Let $C$ be a curve of genus $g$ over a field $k$. We describe probabilistic algorithms for addition and inversion of the classes of rational divisors in the Jacobian of $C$. After a precomputation, which is done only once for the curve $C$,…

Number Theory · Mathematics 2007-08-22 Kamal Khuri-Makdisi

Computing the simulation preorder of a given Kripke structure (i.e., a directed graph with $n$ labeled vertices) has crucial applications in model checking of temporal logic. It amounts to solving a specific two-players reachability game,…

Computational Complexity · Computer Science 2016-08-31 Massimo Cairo , Romeo Rizzi

Fixman's work in 1974 and the follow-up studies have developed a method that can factorize the inverse of mass matrix into an arithmetic combination of three sparse matrices---one of them is positive definite and need to be further…

Computational Physics · Physics 2017-09-13 Xiankun Xu , Peiwen Li

M\"obius inversion of functions on partially ordered sets (posets) $\mathcal{P}$ is a classical tool in combinatorics. For finite posets it consists of two, mutually inverse, linear transformations called zeta and M\"obius transform,…

Discrete Mathematics · Computer Science 2022-11-28 Tommaso Pegolotti , Bastian Seifert , Markus Püschel

The large sparse linear systems arising from the finite element or finite difference discretization of elliptic PDEs can be solved directly via, e.g., nested dissection or multifrontal methods. Such techniques reorder the nodes in the grid…

Numerical Analysis · Mathematics 2013-02-26 Adrianna Gillman , Per-Gunnar Martinsson

We describe a C implementation of the Las Vegas algorithm of Birmpilis, Labahn and Storjohann from 2020 for computing the Smith normal form of a nonsingular integer matrix. The algorithm computes a Smith massager for the input matrix using…

Mathematical Software · Computer Science 2026-05-20 Ziwen Wang , Stavros Birmpilis , George Labahn , Arne Storjohann

This paper investigates the distributed computation of the well-known linear matrix equation in the form of $AXB = F$, with the matrices A, B, X, and F of appropriate dimensions, over multi-agent networks from an optimization perspective.…

Optimization and Control · Mathematics 2018-06-12 Xianlin Zeng , Shu Liang , Yiguang Hong , Jie Chen

The computational cost of transfer matrix methods for the Potts model is directly related to the problem of \textit{into how many ways can two adjacent blocks of a lattice be connected}. Answering this question leads to the generation of a…

Computational Physics · Physics 2016-08-10 Cristobal A. Navarro , Fabrizio Canfora , Nancy Hitschfeld Kahler , Gonzalo Navarro