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Chang's lemma (Duke Mathematical Journal, 2002) is a classical result with applications across several areas in mathematics and computer science. For a Boolean function $f$ that takes values in {-1,1} let $r(f)$ denote its Fourier rank. For…

Computational Complexity · Computer Science 2021-05-25 Sourav Chakraborty , Nikhil S. Mande , Rajat Mittal , Tulasimohan Molli , Manaswi Paraashar , Swagato Sanyal

We consider the problem of testing whether an unknown Boolean function $f$ is monotone versus $\epsilon$-far from every monotone function. The two main results of this paper are a new lower bound and a new algorithm for this well-studied…

Computational Complexity · Computer Science 2014-12-19 Xi Chen , Rocco A. Servedio , Li-Yang Tan

Boolean functions with few-valued spectra have wide applications in cryptography, coding theory, sequence designs, etc. In this paper, we further study the parametric construction approach to obtain balanced Boolean functions using…

Information Theory · Computer Science 2025-06-25 Qiancheng Zhang , Kangquan Li , Longjiang Qu

We study Boolean functions with sparse Fourier coefficients or small spectral norm, and show their applications to the Log-rank Conjecture for XOR functions f(x\oplus y) --- a fairly large class of functions including well studied ones such…

Computational Complexity · Computer Science 2013-04-10 Hing Yin Tsang , Chung Hoi Wong , Ning Xie , Shengyu Zhang

Let $\mathsf{TH}_k$ denote the $k$-out-of-$n$ threshold function: given $n$ input Boolean variables, the output is $1$ if and only if at least $k$ of the inputs are $1$. We consider the problem of computing the $\mathsf{TH}_k$ function…

Data Structures and Algorithms · Computer Science 2024-12-24 Ziao Wang , Nadim Ghaddar , Banghua Zhu , Lele Wang

We establish new upper and lower bounds on the number of queries required to test convexity of functions over various discrete domains. 1. We provide a simplified version of the non-adaptive convexity tester on the line. We re-prove the…

Computational Complexity · Computer Science 2019-08-08 Aleksandrs Belovs , Eric Blais , Abhinav Bommireddi

Smoothness of a function $f:{\mathbb R}^n\to {\mathbb R}$ can be measured in terms of the rate of convergence of $f\ast\rho_\varepsilon$ to $f$, where $\rho$ is an appropriate mollifier. In the framework of fractional Sobolev spaces, we…

Functional Analysis · Mathematics 2014-04-29 Xavier Lamy , Petru Mironescu

For $S \subseteq \{0,1\}^n$ a Boolean function $f \colon S \to \{-1,1\}$ is a polynomial threshold function (PTF) of degree $d$ and weight $W$ if there is a polynomial $p$ with integer coefficients of degree $d$ and with sum of absolute…

Computational Complexity · Computer Science 2022-12-22 Vladimir Podolskii , Nikolay V. Proskurin

We give a "regularity lemma" for degree-d polynomial threshold functions (PTFs) over the Boolean cube {-1,1}^n. This result shows that every degree-d PTF can be decomposed into a constant number of subfunctions such that almost all of the…

Computational Complexity · Computer Science 2015-03-13 Ilias Diakonikolas , Rocco A. Servedio , Li-Yang Tan , Andrew Wan

We show that for any constant $c>0$, any (two-sided error) adaptive algorithm for testing monotonicity of Boolean functions must have query complexity $\Omega(n^{1/2-c})$. This improves the $\tilde\Omega(n^{1/3})$ lower bound of [CWX17] and…

Computational Complexity · Computer Science 2025-11-10 Mark Chen , Xi Chen , Hao Cui , William Pires , Jonah Stockwell

Boolean functions on the space $F_{2}^m$ are not only important in the theory of error-correcting codes, but also in cryptography, where they occur in private key systems. In these two cases, the nonlinearity of these function is a main…

Number Theory · Mathematics 2015-06-26 Francois Rodier

We prove that every bounded function $f:\{-1,1\}^n\to[-1,1]$ of degree at most $d$ can be learned with $L_2$-accuracy $\varepsilon$ and confidence $1-\delta$ from $\log(\tfrac{n}{\delta})\,\varepsilon^{-d-1} C^{d^{3/2}\sqrt{\log d}}$ random…

Machine Learning · Computer Science 2022-03-10 Alexandros Eskenazis , Paata Ivanisvili

In this report, we show that all n-variable Boolean function can be represented as polynomial threshold functions (PTF) with at most $0.75 \times 2^n$ non-zero integer coefficients and give an upper bound on the absolute value of these…

Discrete Mathematics · Computer Science 2020-07-07 Erhan Oztop , Minoru Asada

We prove a $k^{-\Omega(\log(\varepsilon_2 - \varepsilon_1))}$ lower bound for adaptively testing whether a Boolean function is $\varepsilon_1$-close to or $\varepsilon_2$-far from $k$-juntas. Our results provide the first superpolynomial…

Data Structures and Algorithms · Computer Science 2023-04-24 Xi Chen , Shyamal Patel

We prove lower bounds on complexity measures, such as the approximate degree of a Boolean function and the approximate rank of a Boolean matrix, using quantum arguments. We prove these lower bounds using a quantum query algorithm for the…

Quantum Physics · Physics 2018-07-18 Shalev Ben-David , Adam Bouland , Ankit Garg , Robin Kothari

We study monotonicity testing of functions $f \colon \{0,1\}^d \to \{0,1\}$ using sample-based algorithms, which are only allowed to observe the value of $f$ on points drawn independently from the uniform distribution. A classic result by…

Data Structures and Algorithms · Computer Science 2024-08-21 Hadley Black

Polynomial threshold functions (PTFs) are an important low-complexity class of Boolean functions, with strong connections to learning theory and approximation theory. Recent work on learning and testing PTFs has exploited structural and…

Computational Complexity · Computer Science 2026-04-28 Fan Chang , Joseph Slote , Alexander Volberg , Haonan Zhang

Polynomial representations of Boolean functions over various rings such as $\mathbb{Z}$ and $\mathbb{Z}_m$ have been studied since Minsky and Papert (1969). From then on, they have been employed in a large variety of fields including…

Computational Complexity · Computer Science 2020-05-04 Xiaoming Sun , Yuan Sun , Jiaheng Wang , Kewen Wu , Zhiyu Xia , Yufan Zheng

We give a $2^{\tilde{O}(\sqrt{n}/\epsilon)}$-time algorithm for properly learning monotone Boolean functions under the uniform distribution over $\{0,1\}^n$. Our algorithm is robust to adversarial label noise and has a running time nearly…

Data Structures and Algorithms · Computer Science 2023-03-29 Jane Lange , Ronitt Rubinfeld , Arsen Vasilyan

Consider a point-to-point communication system in which the transmitter holds a binary message of length $m$ and transmits a corresponding codeword of length $n$. The receiver's goal is to recover a Boolean function of that message, where…

Information Theory · Computer Science 2026-04-17 Jingge Zhu , Matthias Frey