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The purpose of this note is to survey a methodology to solve systems of polynomial equations and inequalities. The techniques we discuss use the algebra of multivariate polynomials with coefficients over a field to create large-scale linear…

Optimization and Control · Mathematics 2011-12-08 Jesus A. De Loera , Peter N. Malkin , Pablo A. Parrilo

Several large-scale machine learning tasks, such as data summarization, can be approached by maximizing functions that satisfy submodularity. These optimization problems often involve complex side constraints, imposed by the underlying…

Data Structures and Algorithms · Computer Science 2021-02-15 Francesco Quinzan , Vanja Doskoč , Andreas Göbel , Tobias Friedrich

We give an $O(N\cdot \log N\cdot 2^{O(\log^*N)})$ algorithm for multiplying two $N$-bit integers that improves the $O(N\cdot \log N\cdot \log\log N)$ algorithm by Sch\"{o}nhage-Strassen. Both these algorithms use modular arithmetic.…

Symbolic Computation · Computer Science 2008-09-19 Anindya De , Piyush P Kurur , Chandan Saha , Ramprasad Saptharishi

We develop a computationally efficient and robust algorithm for generating pseudo-random samples from a broad class of smooth probability distributions in one and two dimensions. The algorithm is based on inverse transform sampling with a…

Numerical Analysis · Mathematics 2013-07-05 Sheehan Olver , Alex Townsend

In this paper, we use composite optimization algorithms to solve sigmoid networks. We equivalently transfer the sigmoid networks to a convex composite optimization and propose the composite optimization algorithms based on the linearized…

Optimization and Control · Mathematics 2023-07-10 Huixiong Chen , Qi Ye

We present a new strongly polynomial algorithm for generalized flow maximization that is significantly simpler and faster than the previous strongly polynomial algorithm [V\'egh16]. For the uncapacitated problem formulation, the complexity…

Data Structures and Algorithms · Computer Science 2020-02-14 Neil Olver , László A. Végh

We present a practical and powerful new framework for both unconstrained and constrained submodular function optimization based on discrete semidifferentials (sub- and super-differentials). The resulting algorithms, which repeatedly compute…

Data Structures and Algorithms · Computer Science 2013-08-13 Rishabh Iyer , Stefanie Jegelka , Jeff Bilmes

Polynomial approximations of functions are widely used in scientific computing. In certain applications, it is often desired to require the polynomial approximation to be non-negative (resp. non-positive), or bounded within a given range,…

Numerical Analysis · Mathematics 2024-11-12 Yuan Chen , Dongbin Xiu , Xiangxiong Zhang

In the sparse polynomial multiplication problem, one is asked to multiply two sparse polynomials f and g in time that is proportional to the size of the input plus the size of the output. The polynomials are given via lists of their…

Symbolic Computation · Computer Science 2020-04-22 Vasileios Nakos

Some skew-symmetrizable integer exchange matrices are associated to ideal (tagged) triangulations of marked bordered surfaces. These exchange matrices admits unfoldings to skew-symmetric matrices. We develop an combinatorial algorithm that…

Combinatorics · Mathematics 2012-02-07 Weiwen Gu

In this article, we design fast algorithms for the computation of approximant bases in shifted Popov normal form. We first recall the algorithm known as PM-Basis, which will be our second fundamental engine after polynomial matrix…

Symbolic Computation · Computer Science 2019-04-09 Claude-Pierre Jeannerod , Vincent Neiger , Gilles Villard

We give a new fast method for evaluating sprectral approximations of nonlinear polynomial functionals. We prove that the new algorithm is convergent if the functions considered are smooth enough, under a general assumption on the spectral…

Numerical Analysis · Mathematics 2012-07-17 Erwan Faou , Fabio Nobile , Christophe Vuillot

A systematic construction of higher order splines using two hierarchies of polynomials is presented. Explicit instructions on how to implement one of these hierarchies are given. The results are limited to interpolations on regular,…

Numerical Analysis · Computer Science 2009-05-25 Cristian Constantin Lalescu

Fast matrix multiplication algorithms may be useful, provided that their running time is good in practice. Particularly, the leading coefficient of their arithmetic complexity needs to be small. Many sub-cubic algorithms have large leading…

Data Structures and Algorithms · Computer Science 2020-08-11 Gal Beniamini , Nathan Cheng , Olga Holtz , Elaye Karstadt , Oded Schwartz

We present a highly scalable algorithm for multiplying sparse multivariate polynomials represented in a distributed format. This algo- rithm targets not only the shared memory multicore computers, but also computers clusters or specialized…

Symbolic Computation · Computer Science 2013-04-01 Mickael Gastineau , Jacques Laskar

Fast approximations to matrix multiplication have the potential to dramatically reduce the cost of neural network inference. Recent work on approximate matrix multiplication proposed to replace costly multiplications with table-lookups by…

Machine Learning · Computer Science 2022-07-14 Calvin McCarter , Nicholas Dronen

We present a new improvement on the laser method for designing fast matrix multiplication algorithms. The new method further develops the recent advances by [Duan, Wu, Zhou FOCS 2023] and [Vassilevska Williams, Xu, Xu, Zhou SODA 2024].…

Data Structures and Algorithms · Computer Science 2024-10-22 Josh Alman , Ran Duan , Virginia Vassilevska Williams , Yinzhan Xu , Zixuan Xu , Renfei Zhou

Decimal multiplication is the task of multiplying two numbers in base $10^N.$ Specifically, we focus on the number-theoretic transform (NTT) family of algorithms. Using only portable techniques, we achieve a 3x-5x speedup over the mpdecimal…

Data Structures and Algorithms · Computer Science 2020-12-11 Viktor Krapivensky

This document describes an algorithm to scale a complex vector by the reciprocal of a complex value. The algorithm computes the reciprocal of the complex value and then scales the vector by the reciprocal. Some scaling may be necessary due…

Numerical Analysis · Mathematics 2023-11-13 Weslley da Silva Pereira

We study the cost of multiplication modulo triangular families of polynomials. Following previous work by Li, Moreno Maza and Schost, we propose an algorithm that relies on homotopy and fast evaluation-interpolation techniques. We obtain a…

Symbolic Computation · Computer Science 2009-01-26 Alin Bostan , Muhammad Chowdhury , Joris van der Hoeven , Eric Schost
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