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Related papers: Recovering or Testing Extended-Affine Equivalence

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In recent years, many design automation methods have been developed to routinely create approximate implementations of circuits and programs that show excellent trade-offs between the quality of output and required resources. This paper…

Neural and Evolutionary Computing · Computer Science 2021-08-17 Lukas Sekanina

We associate to each Boolean function a polynomial whose evaluations represents the distances from all possible Boolean affine functions. Both determining the coefficients of this polynomial from the truth table of the Boolean function and…

Information Theory · Computer Science 2014-04-11 Emanuele Bellini

We prove a new structural lemma for partial Boolean functions $f$, which we call the seed lemma for DNF. Using the lemma, we give the first subexponential algorithm for proper learning of DNF in Angluin's Equivalence Query (EQ) model. The…

Machine Learning · Computer Science 2011-11-07 Lisa Hellerstein , Devorah Kletenik , Linda Sellie , Rocco Servedio

We consider the complexity of maximizing egalitarian welfare in Friends and Enemies Games -- a subclass of hedonic games in which every agent partitions other agents into friends and enemies. We investigate two classic scenarios proposed in…

Computer Science and Game Theory · Computer Science 2025-12-24 Edith Elkind , Michele Flammini , Giovanna Varricchio

Consider the operator $E$ on arithmetic functions such that $Ef$ is the multiplicative arithmetic function defined by $(Ef)(p^a) = f(a)$ for every prime power $p^a$. We investigate the behaviour of $E^m\tau_k$, where $\tau_k$ is a…

Number Theory · Mathematics 2015-10-20 Andrew V. Lelechenko

We present a new approach to compute selected eigenvalues and eigenvectors of the two-parameter eigenvalue problem. Our method requires computing generalized eigenvalue problems of the same size as the matrices of the initial two-parameter…

Numerical Analysis · Mathematics 2021-05-12 Henrik Eisenmann , Yuji Nakatsukasa

This paper deals with some nonlinear problems which exponential and biexponential decays are involved in. A proof of the quasiconvexity of the error function in some of these problems of optimization is presented. This proof is restricted…

We study parallel algorithms for the minimisation and equivalence checking of Deterministic Finite Automata (DFAs). Regarding DFA minimisation, we implement four different massively parallel algorithms on Graphics Processing Units~(GPUs).…

Formal Languages and Automata Theory · Computer Science 2025-08-29 Jan Heemstra , Jan Martens , Anton Wijs

Repair operators are often used for constraint handling in constrained combinatorial optimization. We investigate the (1+1)~EA equipped with a tailored jump-and-repair operation that can be used to probabilistically repair infeasible…

Neural and Evolutionary Computing · Computer Science 2023-01-24 Luke Branson , Andrew M. Sutton

We investigate the affine equivalence (AE) problem of S-boxes. Given two S-boxes denoted as $S_1$ and $S_2$, we aim to seek two invertible AE transformations $A,B$ such that $S_1\circ A = B\circ S_2$ holds. Due to important applications in…

Cryptography and Security · Computer Science 2024-11-20 Xincheng Hu , Xiao Zeng , Zhaoqiang Liu , Guowu Yang

Function association is a useful process for binary reverse engineers. Search tools exist to perform association at scale, but they do not utilize the full range of capabilities that AI-enabled search provides. Prior work has explored the…

Cryptography and Security · Computer Science 2026-05-08 Eric Wolos , Michael Doyle

Quaternionic signal processing provides powerful tools for efficiently managing color signals by preserving the intrinsic correlations among signal dimensions through quaternion algebra. In this paper, we address the quaternionic phase…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Ren Hu , Pan Lian

A problem based on the Extended Euclidean Algorithm applied to a class of polynomials with many factors is presented and believed to be hard. If so, it is a one-way function well suited for applications in digital signicatures.

Cryptography and Security · Computer Science 2008-01-16 Ephraim Feig , Vivian Feig

The problem to compute the vertices of a polytope given by affine inequalities is called vertex enumeration. The inverse problem, which is equivalent by polarity, is called the convex hull problem. We introduce `approximate vertex…

Optimization and Control · Mathematics 2024-01-26 Andreas Löhne

We study fair division of indivisible items under a variable input setting, where the set of agents or items may change over time. Starting from an arbitrary allocation, the goal is to restore envy-freeness up to one item (EF1) through item…

Computer Science and Game Theory · Computer Science 2026-04-28 Harish Chandramouleeswaran , Prajakta Nimbhorkar , Nidhi Rathi

Electrical Impedance Tomography (EIT) is widely applied in medical diagnosis, industrial inspection, and environmental monitoring. Combining the physical principles of the imaging system with the advantages of data-driven deep learning…

Computer Vision and Pattern Recognition · Computer Science 2024-02-27 Guixian Xu , Huihui Wang , Qingping Zhou

Soft extrapolation refers to the problem of recovering a function from its samples, multiplied by a fast-decaying window and perturbed by an additive noise, over an interval which is potentially larger than the essential support of the…

Numerical Analysis · Mathematics 2018-12-26 Dmitry Batenkov , Laurent Demanet , Hrushikesh N. Mhaskar

This paper analyzes the iteration-complexity of a quadratic penalty accelerated inexact proximal point method for solving linearly constrained nonconvex composite programs. More specifically, the objective function is of the form $f + h$…

Optimization and Control · Mathematics 2019-07-17 Weiwei Kong , Jefferson G. Melo , Renato D. C. Monteiro

We introduce a new discriminant analysis method (Empirical Discriminant Analysis or EDA) for binary classification in machine learning. Given a dataset of feature vectors, this method defines an empirical feature map transforming the…

Machine Learning · Statistics 2012-10-30 Mark A. Kon , Nikolay Nikolaev

Proximal operators are fundamental across many applications in signal processing and machine learning, including solving ill-posed inverse problems. Recent work has introduced Learned Proximal Networks (LPNs), providing parametric functions…

Machine Learning · Computer Science 2026-04-20 Oriel Savir , Zhenghan Fang , Jeremias Sulam