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I present a simple dynamic programming algorithm for the evaluation of operators in a wide range of superconformal algebras. Special care is taken to describe the computation of the Gram matrix. A Mathematica package, Weaver.m, is provided…

High Energy Physics - Theory · Physics 2015-08-19 Daniel Whalen

Genetic algorithms are heuristic optimization techniques inspired by Darwinian evolution, which are characterized by successfully finding robust solutions for optimization problems. Here, we propose a subroutine-based quantum genetic…

Quantum Physics · Physics 2024-06-07 Rubén Ibarrondo , Giancarlo Gatti , Mikel Sanz

A family of loss functions built on pair-based computation have been proposed in the literature which provide a myriad of solutions for deep metric learning. In this paper, we provide a general weighting framework for understanding recent…

Computer Vision and Pattern Recognition · Computer Science 2020-03-24 Xun Wang , Xintong Han , Weilin Huang , Dengke Dong , Matthew R. Scott

We propose a new polynomial-time algorithm for linear programming. We further extend the ideas used in this new linear programming algorithm for nonlinear programming problems. The new algorithm is based on the idea of treating the…

General Mathematics · Mathematics 2019-03-14 Dhananjay P. Mehendale

Graph pattern mining (GPM) is an important application that identifies structures from graphs. Despite the recent progress, the performance gap between the state-of-the-art GPM systems and an efficient algorithm--pattern decomposition--is…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-11-14 Jingji Chen , Xuehai Qian

Using evaluation at appropriately chosen points, we propose a Gr\"obner basis free approach for calculating the secondary invariants of a finite permutation group. This approach allows for exploiting the symmetries to confine the…

Combinatorics · Mathematics 2011-10-19 Nicolas Borie , Nicolas M. Thiéry

The Conjugate Gradient method (CGM) is known to be the fastest generic iterative method for solving linear systems with symmetric sign definite matrices. In this paper, we modify this method so that it could find fundamental solitary waves…

Pattern Formation and Solitons · Physics 2015-05-13 Taras I. Lakoba

The computation of Gr\"obner bases is an established hard problem. By contrast with many other problems, however, there has been little investigation of whether this hardness is robust. In this paper, we frame and present results on the…

Symbolic Computation · Computer Science 2018-07-18 Gwen Spencer , David Rolnick

We present a new algorithm for computing a $\mu$-basis of the syzygy module of $n$ polynomials in one variable over an arbitrary field $\mathbb{K}$. The algorithm is conceptually different from the previously-developed algorithms by Cox,…

Algebraic Geometry · Mathematics 2017-03-09 Hoon Hong , Zachary Hough , Irina A. Kogan

Faugere's F5 algorithm computes a Groebner basis incrementally, by computing a sequence of (non-reduced) Groebner bases. The authors describe a variant of F5, called F5C, that replaces each intermediate Groebner basis with its reduced…

Commutative Algebra · Mathematics 2011-05-19 Christian Eder , John Perry

The concept of generalized cross-validation (GCV) is applied to modified total generalized variation (MTGV) regularization. Current implementations of the MTGV regularization rely on manual (or semi-manual) hyperparameter optimization,…

Given a weighted bipartite graph $G = (L, R, E, w)$, the maximum weight matching (MWM) problem seeks to find a matching $M \subseteq E$ that maximizes the total weight $\sum_{e \in M} w(e)$. This paper presents a novel algorithm with a time…

Data Structures and Algorithms · Computer Science 2025-04-07 Shawxing Kwok

We report on our experiences exploring state of the art Groebner basis computation. We investigate signature based algorithms in detail. We also introduce new practical data structures and computational techniques for use in both signature…

Symbolic Computation · Computer Science 2012-07-02 Bjarke Hammersholt Roune , Michael Stillman

Arora & Ge introduced a noise-free polynomial system to compute the secret of a Learning With Errors (LWE) instance via linearization. Albrecht et al. later utilized the Arora-Ge polynomial model to study the complexity of Gr\"obner basis…

Cryptography and Security · Computer Science 2025-04-01 Matthias Johann Steiner

The performance of graph programs depends highly on the algorithm, the size and structure of the input graphs, as well as the features of the underlying hardware. No single set of optimizations or one hardware platform works well across all…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-01-11 Ajay Brahmakshatriya , Yunming Zhang , Changwan Hong , Shoaib Kamil , Julian Shun , Saman Amarasinghe

The Metropolis-within-Gibbs (MwG) algorithm is a widely used Markov Chain Monte Carlo method for sampling from high-dimensional distributions when exact conditional sampling is intractable. We study MwG with Random Walk Metropolis (RWM)…

Machine Learning · Statistics 2025-10-01 Cecilia Secchi , Giacomo Zanella

Polynomial preconditioning can improve the convergence of the Arnoldi method for computing eigenvalues. Such preconditioning significantly reduces the cost of orthogonalization; for difficult problems, it can also reduce the number of…

Numerical Analysis · Mathematics 2018-06-22 Mark Embree , Jennifer A. Loe , Ronald B. Morgan

To implement the Wigner branching random walk, the particle carrying a signed weight, either $-1$ or $+1$, is more friendly to data storage and arithmetic manipulations than that taking a real-valued weight continuously from $-1$ to $+1$.…

Computational Physics · Physics 2019-06-04 Yunfeng Xiong , Sihong Shao

Global Value Numbering (GVN) is an important static analysis to detect equivalent expressions in a program. We present an iterative data-flow analysis GVN algorithm in SSA for the purpose of detecting total redundancies. The central…

Programming Languages · Computer Science 2015-04-14 Rekha R Pai

Multi-parameter persistent homology is a recent branch of topological data analysis. In this area, data sets are investigated through the lens of homology with respect to two or more scale parameters. The high computational cost of many…

Algebraic Topology · Mathematics 2020-10-30 Michael Kerber , Alexander Rolle