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The model of relative-error property testing of Boolean functions has been the subject of significant recent research effort [CDH+24][CPPS25a][CPPS25b] In this paper we consider the problem of relative-error testing an unknown and arbitrary…

Computational Complexity · Computer Science 2025-10-27 Xi Chen , Diptaksho Palit , Kabir Peshawaria , William Pires , Rocco A. Servedio , Yiding Zhang

We study the relative-error property testing model for Boolean functions that was recently introduced in the work of Chen et al. (SODA 2025). In relative-error testing, the testing algorithm gets uniform random satisfying assignments as…

Computational Complexity · Computer Science 2025-04-15 Xi Chen , William Pires , Toniann Pitassi , Rocco A. Servedio

We give the first algorithm that is both query-efficient and time-efficient for testing whether an unknown function $f: \{0,1\}^n \to \{0,1\}$ is an $s$-sparse GF(2) polynomial versus $\eps$-far from every such polynomial. Our algorithm…

Computational Complexity · Computer Science 2008-05-14 Ilias Diakonikolas , Homin K. Lee , Kevin Matulef , Rocco A. Servedio , Andrew Wan

In this paper, we study the problem of learning a monotone DNF with at most $s$ terms of size (number of variables in each term) at most $r$ ($s$ term $r$-MDNF) from membership queries. This problem is equivalent to the problem of learning…

Machine Learning · Computer Science 2014-05-06 Hasan Abasi , Nader H. Bshouty , Hanna Mazzawi

We give improved and almost optimal testers for several classes of Boolean functions on $n$ inputs that have concise representation in the uniform and distribution-free model. Classes, such as $k$-junta, $k$-linear functions, $s$-term DNF,…

Data Structures and Algorithms · Computer Science 2023-06-22 Nader H. Bshouty

We give two results on PAC learning DNF formulas using membership queries in the challenging "distribution-free" learning framework, where learning algorithms must succeed for an arbitrary and unknown distribution over $\{0,1\}^n$. (1) We…

Data Structures and Algorithms · Computer Science 2025-05-27 Josh Alman , Shivam Nadimpalli , Shyamal Patel , Rocco A. Servedio

Several recent works [DHLNSY25, CPPS25a, CPPS25b] have studied a model of property testing of Boolean functions under a \emph{relative-error} criterion. In this model, the distance from a target function $f: \{0,1\}^n \to \{0,1\}$ that is…

Computational Complexity · Computer Science 2026-03-24 Xi Chen , Anindya De , Yizhi Huang , Shivam Nadimpalli , Rocco A. Servedio , Tianqi Yang

We study the problem of testing whether a function $f: \mathbb{R}^n \to \mathbb{R}$ is a polynomial of degree at most $d$ in the \emph{distribution-free} testing model. Here, the distance between functions is measured with respect to an…

Data Structures and Algorithms · Computer Science 2022-04-19 Vipul Arora , Arnab Bhattacharyya , Noah Fleming , Esty Kelman , Yuichi Yoshida

This papers considers the junta testing problem in a recently introduced ``relative error'' variant of the standard Boolean function property testing model. In relative-error testing we measure the distance from $f$ to $g$, where $f,g:…

Computational Complexity · Computer Science 2025-04-15 Xi Chen , William Pires , Toniann Pitassi , Rocco A. Servedio

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 prove that any submodular function f: {0,1}^n -> {0,1,...,k} can be represented as a pseudo-Boolean 2k-DNF formula. Pseudo-Boolean DNFs are a natural generalization of DNF representation for functions with integer range. Each term in…

Machine Learning · Computer Science 2012-08-14 Sofya Raskhodnikova , Grigory Yaroslavtsev

Configurable systems typically consist of reusable assets that have dependencies between each other. To specify such dependencies, feature models are commonly used. As feature models in practice are often complex, automated reasoning is…

Artificial Intelligence · Computer Science 2025-05-12 Chico Sundermann , Stefan Vill , Elias Kuiter , Sebastian Krieter , Thomas Thüm , Matthias Tichy

The standard model of Boolean function property testing is not well suited for testing $\textit{sparse}$ functions which have few satisfying assignments, since every such function is close (in the usual Hamming distance metric) to the…

Computational Complexity · Computer Science 2025-09-03 Xi Chen , Anindya De , Yizhi Huang , Yuhao Li , Shivam Nadimpalli , Rocco A. Servedio , Tianqi Yang

We give a $\mathrm{poly}(\log n, 1/\epsilon)$-query adaptive algorithm for testing whether an unknown Boolean function $f: \{-1,1\}^n \to \{-1,1\}$, which is promised to be a halfspace, is monotone versus $\epsilon$-far from monotone. Since…

Computational Complexity · Computer Science 2017-06-20 Xi Chen , Rocco A. Servedio , Li-Yang Tan , Erik Waingarten

We provide the first fully polynomial-time randomized approximation scheme for the following two counting problems: 1. Given a Context Free Grammar $G$ over alphabet $\Sigma$, count the number of words of length exactly $n$ generated by…

Data Structures and Algorithms · Computer Science 2026-05-18 Kuldeep S. Meel , Alexis de Colnet

We prove that any non-adaptive algorithm that tests whether an unknown Boolean function $f: \{0, 1\}^n\to \{0, 1\}$ is a $k$-junta or $\epsilon$-far from every $k$-junta must make $\widetilde{\Omega}(k^{3/2} / \epsilon)$ many queries for a…

Computational Complexity · Computer Science 2017-04-24 Xi Chen , Rocco A. Servedio , Li-Yang Tan , Erik Waingarten , Jinyu Xie

We consider the Stochastic Boolean Function Evaluation (SBFE) problem where the task is to efficiently evaluate a known Boolean function $f$ on an unknown bit string $x$ of length $n$. We determine $f(x)$ by sequentially testing the…

Data Structures and Algorithms · Computer Science 2022-08-09 Lisa Hellerstein , Devorah Kletenik , Naifeng Liu , R. Teal Witter

Let $\mathcal{P}$ be a property of function $\mathbb{F}_p^n \to \{0,1\}$ for a fixed prime $p$. An algorithm is called a tester for $\mathcal{P}$ if, given a query access to the input function $f$, with high probability, it accepts when $f$…

Computational Complexity · Computer Science 2014-02-11 Yuichi Yoshida

The best current methods for exactly computing the number of satisfying assignments, or the satisfying probability, of Boolean formulas can be seen, either directly or indirectly, as building 'decision-DNNF' (decision decomposable negation…

Databases · Computer Science 2013-09-27 Paul Beame , Jerry Li , Sudeepa Roy , Dan Suciu

This is the latest in a series of articles aimed at exploring the relationship between the complexity classes of P and NP. In the previous papers, we have proved that the sat CNF problem is polynomially reduced to the problem of finding a…

Computational Complexity · Computer Science 2023-11-01 Stepan G. Margaryan
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