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Solving systems of Boolean equations is a fundamental task in symbolic computation and algebraic cryptanalysis, with wide-ranging applications in cryptography, coding theory, and formal verification. Among existing approaches, the Boolean…

Cryptography and Security · Computer Science 2026-04-21 Minzhong Luo , Yudong Sun , Yin Long

We give a deterministic, polynomial-time algorithm for approximately counting the number of {0,1}-solutions to any instance of the knapsack problem. On an instance of length n with total weight W and accuracy parameter eps, our algorithm…

Data Structures and Algorithms · Computer Science 2010-08-20 Parikshit Gopalan , Adam Klivans , Raghu Meka

Finding balanced, highly nonlinear Boolean functions is a difficult problem where it is not known what nonlinearity values are possible to be reached in general. At the same time, evolutionary computation is successfully used to evolve…

Neural and Evolutionary Computing · Computer Science 2022-02-18 Claude Carlet , Marko Djurasevic , Domagoj Jakobovic , Luca Mariot , Stjepan Picek

Block-structured integer linear programs (ILPs) play an important role in various application fields. We address $n$-fold ILPs where the matrix $\mathcal{A}$ has a specific structure, i.e., where the blocks in the lower part of…

Data Structures and Algorithms · Computer Science 2025-10-13 Klaus Jansen , Kai Kahler , Lis Pirotton , Malte Tutas

We study a broad class of algorithmic problems with an "additive flavor" such as computing sumsets, 3SUM, Subset Sum and geometric pattern matching. Our starting point is that these problems can often be solved efficiently for integers,…

Data Structures and Algorithms · Computer Science 2024-10-30 Nick Fischer

This paper presents a deterministic algorithmic approach of exploring the solution space of the Subset Sum Problem. The algorithm presented is input-robust and structurally adaptive. Exploration is guided and narrows into areas in the…

Computational Complexity · Computer Science 2025-06-19 Thami Nkosi

Two contrasting algorithmic paradigms for constraint satisfaction problems are successive local explorations of neighboring configurations versus producing new configurations using global information about the problem (e.g. approximating…

Quantum Physics · Physics 2022-12-09 S. Andrew Lanham

We present a new framework for the fast solution of inhomogeneous elliptic boundary value problems in domains with smooth boundaries. High-order solvers based on adaptive box codes or the fast Fourier transform can efficiently treat the…

Numerical Analysis · Mathematics 2025-01-31 Daniel Fortunato , David B. Stein , Alex H. Barnett

A novel approach to Boolean matrix factorization (BMF) is presented. Instead of solving the BMF problem directly, this approach solves a nonnegative optimization problem with the constraint over an auxiliary matrix whose Boolean structure…

Data Structures and Algorithms · Computer Science 2021-08-27 Duc P. Truong , Erik Skau , Derek Desantis , Boian Alexandrov

The discrete acyclic convolution computes the 2n-1 sums sum_{i+j=k; (i,j) in [0,1,2,...,n-1]^2} (a_i b_j) in O(n log n) time. By using suitable offsets and setting some of the variables to zero, this method provides a tool to calculate all…

Data Structures and Algorithms · Computer Science 2019-10-28 Mitsuru Funakoshi , Julian Pape-Lange

The alternating direction method of multipliers (ADMM) has recently sparked interest as a flexible and efficient optimization tool for imaging inverse problems, namely deconvolution and reconstruction under non-smooth convex regularization.…

Optimization and Control · Mathematics 2015-06-11 Mariana S. C. Almeida , Mário A. T. Figueiredo

This paper focuses on the problem of evolving Boolean functions of odd sizes with high nonlinearity, a property of cryptographic relevance. Despite its simple formulation, this problem turns out to be remarkably difficult. We perform a…

Neural and Evolutionary Computing · Computer Science 2025-04-25 Claude Carlet , Marko Đurasevic , Domagoj Jakobovic , Stjepan Picek , Luca Mariot

We study the parameterized complexity of algorithmic problems whose input is an integer set $A$ in terms of the doubling constant $C := |A + A|/|A|$, a fundamental measure of additive structure. We present evidence that this new…

Data Structures and Algorithms · Computer Science 2024-07-26 Tim Randolph , Karol Węgrzycki

The problem of approximately computing the $k$ dominant Fourier coefficients of a vector $X$ quickly, and using few samples in time domain, is known as the Sparse Fourier Transform (sparse FFT) problem. A long line of work on the sparse FFT…

Data Structures and Algorithms · Computer Science 2017-04-12 Volkan Cevher , Michael Kapralov , Jonathan Scarlett , Amir Zandieh

We initiate the study of \emph{inverse} problems in approximate uniform generation, focusing on uniform generation of satisfying assignments of various types of Boolean functions. In such an inverse problem, the algorithm is given uniform…

Computational Complexity · Computer Science 2012-11-09 Anindya De , Ilias Diakonikolas , Rocco A. Servedio

We describe a fast algorithm for computing discrete Hankel transforms of moderate orders from $n$ nonuniform points to $m$ nonuniform frequencies in $O((m+n)\log\min(n,m))$ operations. Our approach combines local and asymptotic Bessel…

Numerical Analysis · Mathematics 2024-11-15 Paul G. Beckman , Michael O'Neil

This work illustrates the possibility to apply the Fast Fourier Transformation to obtain the integrals of the Boundary Element Method (BEM) on arbitrary shapes. The procedure is inspired by the technique used with great success within the…

Computational Physics · Physics 2018-09-05 Justus Benad

In this paper, we consider a general notion of convolution. Let $D$ be a finite domain and let $D^n$ be the set of $n$-length vectors (tuples) of $D$. Let $f : D \times D \to D$ be a function and let $\oplus_f$ be a coordinate-wise…

Data Structures and Algorithms · Computer Science 2023-01-31 Barış Can Esmer , Ariel Kulik , Dániel Marx , Philipp Schepper , Karol Węgrzycki

Bayesian posterior inference is prevalent in various machine learning problems. Variational inference provides one way to approximate the posterior distribution, however its expressive power is limited and so is the accuracy of resulting…

Machine Learning · Computer Science 2018-07-11 Guoqing Zheng , Yiming Yang , Jaime Carbonell

The "Subset Sum problem" is a very well-known NP-complete problem. In this work, a top-k variation of the "Subset Sum problem" is considered. This problem has wide application in recommendation systems, where instead of k best objects the k…

Data Structures and Algorithms · Computer Science 2021-08-27 Biswajit Sanyal , Subhashis Majumder , Priya Ranjan Sinha Mahapatra