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We present a non-commutative algorithm for the multiplication of a 2 x 2 block-matrix by its adjoint, defined by a matrix ring anti-homomorphism. This algorithm uses 5 block products (3 recursive calls and 2 general products)over C or in…

Symbolic Computation · Computer Science 2021-01-05 Jean-Guillaume Dumas , Clément Pernet , Alexandre Sedoglavic

Shor's algorithm for integer factorization offers an exponential speedup over classical methods but remains impractical on Noisy Intermediate Scale Quantum (NISQ) hardware due to the need for many coherent qubits and very deep circuits.…

Quantum Physics · Physics 2025-12-09 Alok Shukla , Prakash Vedula

In this paper, we introduce a Lagrange multiplier approach to construct linearly implicit energy-preserving schemes of arbitrary order for general Hamiltonian PDEs. Unlike the widely used auxiliary variable methods, this novel approach does…

Numerical Analysis · Mathematics 2026-01-21 Yonghui Bo , Yushun Wang

In 1969 Strassen showed surprisingly that it is possible to multiply two 2 x 2 matrices using seven multiplications and 18 additions, instead of the naive eight multiplications and four additions. The number of additions was later reduced…

Symbolic Computation · Computer Science 2026-01-12 Erik Mårtensson , Paul Stankovski Wagner , Joshua Stapleton

Processors may find some elementary operations to be faster than the others. Although an operation may be conceptually as simple as some other operation, the processing speeds of the two can vary. A clever programmer will always try to…

Data Structures and Algorithms · Computer Science 2012-12-27 Rajat Tandon

In modern neural networks like Transformers, linear layers require significant memory to store activations during backward pass. This study proposes a memory reduction approach to perform backpropagation through linear layers. Since the…

Machine Learning · Computer Science 2022-02-04 Daniel Bershatsky , Aleksandr Mikhalev , Alexandr Katrutsa , Julia Gusak , Daniil Merkulov , Ivan Oseledets

Continual learning aims at incrementally acquiring new knowledge while not forgetting existing knowledge. To overcome catastrophic forgetting, methods are either rehearsal-based, i.e., store data examples from previous tasks for data…

Machine Learning · Computer Science 2024-04-02 Mingyang Wang , Heike Adel , Lukas Lange , Jannik Strötgen , Hinrich Schütze

An algorithm counting the number of ones in a binary word is presented running in time $O(\log\log b)$ where $b$ is the number of ones. The operations available include bit-wise logical operations and multiplication.

Data Structures and Algorithms · Computer Science 2015-06-12 Holger Petersen

In this work a rationalized algorithm for calculating the quotient of two complex numbers is presented which reduces the number of underlying real multiplications. The performing of a complex number division using the naive method takes 4…

Data Structures and Algorithms · Computer Science 2016-08-31 Aleksandr Cariow

A novel polynomial expansion method of symmetric Boolean functions is described. The method is efficient for symmetric Boolean function with small set of valued numbers and has the linear complexity for elementary symmetric Boolean…

Discrete Mathematics · Computer Science 2013-06-25 Danila A. Gorodecky

We propose a simple, projection-based algorithm for clustering mixtures of discrete (Bernoulli) distributions. Unlike previous approaches that rely on coordinate-specific ``combinatorial projections,'' our algorithm is rotationally…

Data Structures and Algorithms · Computer Science 2026-04-28 Pradipta Mitra

We analyse and compare the complexity of several algorithms for computing modular polynomials. We show that an algorithm relying on floating point evaluation of modular functions and on interpolation, which has received little attention in…

Number Theory · Mathematics 2009-05-08 Andreas Enge

We show a method for constructing a polynomial interpolating roots' multiplicities of another polynomial, that does not use companion matrices. This leads to a modification to Guersenzvaig--Szechtman square-free decomposition algorithm that…

Symbolic Computation · Computer Science 2017-03-20 Przemysław Koprowski

Modularization is an important architectural principle underlying many types of complex systems. It tends to tame the complexity of systems, to facilitate their management, and to enhance their flexibility with respect to evolution. In…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-09-25 Naftaly Minsky

This paper presents an algorithm for the integer multiplicative inverse (mod $2^w$) which completes in the fewest cycles known for modern microprocessors, when using the native bit width $w$ for the modulus $2^w$. The algorithm is a…

Data Structures and Algorithms · Computer Science 2022-04-26 Jeffrey Hurchalla

We show that assuming the availability of the processor with variable precision arithmetic, we can compute matrix-by-matrix multiplications in $O(N^2log_2N)$ computational complexity. We replace the standard matrix-by-matrix multiplications…

Data Structures and Algorithms · Computer Science 2025-08-19 Maciej Paszyński

In this paper we present a novel derivation for an existing node-based algorithm for distributed optimisation termed the primal-dual method of multipliers (PDMM). In contrast to its initial derivation, in this work monotone operator theory…

Optimization and Control · Mathematics 2017-11-07 Thomas Sherson , Richard Heusdens , W. Bastiaan Kleijn

Deep model merging represents an emerging research direction that combines multiple fine-tuned models to harness their specialized capabilities across different tasks and domains. Current model merging techniques focus on merging all…

Machine Learning · Computer Science 2025-01-17 Anke Tang , Enneng Yang , Li Shen , Yong Luo , Han Hu , Bo Du , Dacheng Tao

This paper introduces the multiplicative variant of the recently proposed asynchronous additive coarse-space correction method. Definition of an asynchronous extension of multiplicative correction is not straightforward, however, our…

Numerical Analysis · Mathematics 2023-12-20 Guillaume Gbikpi-Benissan , Frédéric Magoulès

This paper introduces two architectures for the inference of convolutional neural networks (CNNs). Both architectures exploit weight sparsity and compression to reduce computational complexity and bandwidth. The first architecture uses…

Computer Vision and Pattern Recognition · Computer Science 2020-12-14 Vincenzo Liguori
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