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In this paper, we establish a new inequality tying together the effective length and the maximum correlation between the outputs of an arbitrary pair of Boolean functions which operate on two sequences of correlated random variables. We…

Information Theory · Computer Science 2017-02-07 Farhad Shirani , S. Sandeep Pradhan

This paper gives a dichotomy theorem for the complexity of computing the partition function of an instance of a weighted Boolean constraint satisfaction problem. The problem is parameterised by a finite set F of non-negative functions that…

Computational Complexity · Computer Science 2009-02-23 Martin Dyer , Leslie Ann Goldberg , Mark Jerrum

In a recent result, Knop, Lovett, McGuire and Yuan (STOC 2021) proved the log-rank conjecture for communication complexity, up to log n factor, for any Boolean function composed with AND function as the inner gadget. One of the main tools…

Computational Complexity · Computer Science 2024-06-14 Farzan Byramji , Vatsal Jha , Chandrima Kayal , Rajat Mittal

Sophistication and logical depth are two measures that express how complicated the structure in a string is. Sophistication is defined as the minimal complexity of a computable function that defines a two-part description for the string…

Information Theory · Computer Science 2017-01-30 Luís Antunes , Bruno Bauwens , Andre Souto , Andreia Teixeira

Representations of Boolean functions by real polynomials play an important role in complexity theory. Typically, one is interested in the least degree of a polynomial p(x_1,...,x_n) that approximates or sign-represents a given Boolean…

Computational Complexity · Computer Science 2008-05-15 Alexander A. Sherstov

A novel elastic time distance for sparse multivariate functional data is proposed and used to develop a robust distance-based two-layer partition clustering method. With this proposed distance, the new approach not only can detect correct…

Methodology · Statistics 2023-03-21 Zhuo Qu , Wenlin Dai , Marc G. Genton

The approximate degree of a Boolean function $f: \{-1, 1\}^n \to \{-1, 1\}$ is the minimum degree of a real polynomial that approximates $f$ to within error $1/3$ in the $\ell_\infty$ norm. In an influential result, Aaronson and Shi (J. ACM…

Computational Complexity · Computer Science 2015-03-27 Mark Bun , Justin Thaler

We pursue a systematic study of the following problem. Let f:{0,1}^n -> {0,1} be a (usually monotone) Boolean function whose behaviour is well understood when the input bits are identically independently distributed. What can be said about…

Probability · Mathematics 2012-01-17 Itai Benjamini , Ori Gurel-Gurevich , Ron Peled

In this note, we consider the minimum number of NOT operators in a Boolean formula representing a Boolean function. In circuit complexity theory, the minimum number of NOT gates in a Boolean circuit computing a Boolean function $f$ is…

Computational Complexity · Computer Science 2008-11-06 Hiroki Morizumi

In this paper we study the separation between the deterministic (classical) query complexity ($D$) and the exact quantum query complexity ($Q_E$) of several Boolean function classes using the parity decision tree method. We first define the…

Quantum Physics · Physics 2020-09-07 Chandra Sekhar Mukherjee , Subhamoy Maitra

A random walk-based method is proposed to efficiently compute the solution of a large class of fractional in time linear systems of differential equations (linear F-ODE systems), along with the derivatives with respect to the system…

Numerical Analysis · Mathematics 2024-08-09 Andrés Centeno , Juan A. Acebrón , José Monteiro

In this paper, we perform sensitivity analysis for the maximal value function which is the optimal value function for a parametric maximization problem. Our aim is to study various subdifferentials for the maximal value function. We obtain…

Optimization and Control · Mathematics 2023-03-03 L. Guo , J. J. Ye , J. Zhang

We give two approximation algorithms solving the Stochastic Boolean Function Evaluation (SBFE) problem for symmetric Boolean functions. The first is an $O(\log n)$-approximation algorithm, based on the submodular goal-value approach of…

Data Structures and Algorithms · Computer Science 2022-01-05 Dimitrios Gkenosis , Nathaniel Grammel , Lisa Hellerstein , Devorah Kletenik

Polynomial threshold gates are basic processing units of an artificial neural network. When the input vectors are binary vectors, these gates correspond to Boolean functions and can be analyzed via their polynomial representations. In…

Computational Complexity · Computer Science 2013-07-05 Yi Ming Zou

Dempster-Shafer theory is widely applied in uncertainty modelling and knowledge reasoning due to its ability of expressing uncertain information. A distance between two basic probability assignments(BPAs) presents a measure of performance…

Artificial Intelligence · Computer Science 2014-04-15 Meizhu Li , Qi Zhang , Xinyang Deng , Yong Deng

A function $f$ is $d$-resilient if all its Fourier coefficients of degree at most $d$ are zero, i.e., $f$ is uncorrelated with all low-degree parities. We study the notion of $\mathit{approximate}$ $\mathit{resilience}$ of Boolean…

Machine Learning · Computer Science 2014-07-10 Dana Dachman-Soled , Vitaly Feldman , Li-Yang Tan , Andrew Wan , Karl Wimmer

We consider the pairing Hamiltonian and systematically construct its density functional in the strong-coupling limit and in the limit of large particle number. In the former limit, the functional is an expansion into central moments of…

Nuclear Theory · Physics 2008-11-26 T. Papenbrock , Anirban Bhattacharyya

Dominant areas of computer science and computation systems are intensively linked to the hypercube-related studies and interpretations. This article presents some transformations and analytics for some example algorithms and Boolean domain…

Discrete Mathematics · Computer Science 2024-02-05 Levon Aslanyan , Irina Arsenyan , Vilik Karakhanyan , Hasmik Sahakyan

In this work, we consider a new type of Fourier-like representation of Boolean function $f\colon\{+1,-1\}^n\to\{+1,-1\}$ \[ f(x) = \cos\left(\pi\sum_{S\subseteq[n]}\phi_S \prod_{i\in S} x_i\right). \] This representation, which we call the…

Quantum Physics · Physics 2019-03-27 Ryuhei Mori

Block sparsity is a widely exploited structure in sparse recovery, offering significant gains when signal blocks are known. Yet, practical signals often exhibit unknown block boundaries and isolated non-zero entries, which challenge…

Signal Processing · Electrical Eng. & Systems 2026-02-05 Yanbin He , Geethu Joseph