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The equivalence of the characteristic function approach and the probabilistic approach to monotone and boolean convolutions is proven for non-compactly supported probability measures. A probabilistically motivated definition of the…

Functional Analysis · Mathematics 2021-04-21 Uwe Franz

This paper is a contribution to the study of a quasi-order on the set $\Omega$ of Boolean functions, the \emph{simple minor} quasi-order. We look at the join-irreducible members of the resulting poset $\tilde{\Omega}$. Using a two-way…

Combinatorics · Mathematics 2008-01-21 Moncef Bouaziz , Miguel Couceiro , Maurice Pouzet

A key fact in the theory of Boolean functions $f : \{0,1\}^n \to \{0,1\}$ is that they often undergo sharp thresholds. For example: if the function $f : \{0,1\}^n \to \{0,1\}$ is monotone and symmetric under a transitive action with…

Combinatorics · Mathematics 2010-11-17 Gil Kalai , Elchanan Mossel

First of all we give some reasons that "natural proofs" built not a barrier to prove P $\not=$ NP using Boolean complexity. Then we investigate the approximation method for its extension to prove super-polynomial lower bounds for the…

Computational Complexity · Computer Science 2020-06-16 Norbert Blum

This paper presents a mistake in work function algorithm of k-server conjecture. That is, the monotonicity of the work function is not always true.

Data Structures and Algorithms · Computer Science 2008-08-26 Ming-Zhe Chen

In the decision tree computation model for Boolean functions, the depth corresponds to query complexity, and size corresponds to storage space. The depth measure is the most well-studied one, and is known to be polynomially related to…

Computational Complexity · Computer Science 2022-09-27 Yogesh Dahiya , Meena Mahajan

We establish new separations between the power of monotone and general (non-monotone) Boolean circuits: - For every $k \geq 1$, there is a monotone function in ${\sf AC^0}$ that requires monotone circuits of depth $\Omega(\log^k n)$. This…

Computational Complexity · Computer Science 2023-05-12 Bruno P. Cavalar , Igor C. Oliveira

We consider the problem of enumerating relevant features hidden in other irrelevant information for multi-labeled data, which is formalized as learning juntas. A $k$-junta function is a function which depends on only $k$ coordinates of the…

Machine Learning · Computer Science 2019-07-16 Mikito Nanashima

We present an adaptive algorithm with one-sided error for the problem of junta testing for Boolean function under the challenging distribution-free setting, the query complexity of which is $\widetilde O(k)/\epsilon$. This improves the…

Computational Complexity · Computer Science 2023-01-27 Xiaojin Zhang

We introduce a novel algorithm that converges to level-set convex viscosity solutions of high-dimensional Hamilton-Jacobi equations. The algorithm is applicable to a broad class of curvature motion PDEs, as well as a recently developed…

Numerical Analysis · Mathematics 2023-11-15 Jeff Calder , Wonjun Lee

A Boolean function f of n variables is said to be q-locally correctable if, given a black-box access to a function g which is "close" to an isomorphism f_sigma(x)=f_sigma(x_1, ..., x_n) = f(x_sigma(1), ..., x_sigma(n)) of f, we can compute…

Computational Complexity · Computer Science 2012-10-23 Noga Alon , Amit Weinstein

We use discrete holomorphic polynomials to prove that, given a refining sequence of critical maps of a Riemann surface, any holomorphic function can be approximated by a converging sequence of discrete holomorphic functions.

Mathematical Physics · Physics 2007-05-23 Christian Mercat

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 show improved monotonicity testers for the Boolean hypercube under the $p$-biased measure, as well as over the hypergrid $[m]^n$. Our results are: 1. For any $p\in (0,1)$, for the $p$-biased hypercube we show a non-adaptive tester that…

Computational Complexity · Computer Science 2022-11-18 Mark Braverman , Subhash Khot , Guy Kindler , Dor Minzer

We prove two conjectures on correlation inequalities for functions that are linear combinations of unimodal Boolean monotone nondecreasing functions

Combinatorics · Mathematics 2014-08-29 Vladimir Blinovsky

This paper is a contribution to the study of a quasi-order on the set $\Omega$ of Boolean functions, the \emph{simple minor} quasi-order. We look at the join-irreducible members of the resulting poset $\tilde{\Omega}$. Using a two-way…

Combinatorics · Mathematics 2009-03-24 Moncef Bouaziz , Miguel Couceiro , Maurice Pouzet

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

The approximate degree of a Boolean function is the minimum degree of real polynomial that approximates it pointwise. For any Boolean function, its approximate degree serves as a lower bound on its quantum query complexity, and generically…

Computational Complexity · Computer Science 2023-05-23 Mark Bun , Nadezhda Voronova

Suppose that $f$ belongs to a suitably defined complete metric space $ {{\cal C}}^{{\alpha}}$ of H\"older $ {\alpha}$-functions defined on $[0,1]$. We are interested in whether one can find large (in the sense of Hausdorff, or lower/upper…

Classical Analysis and ODEs · Mathematics 2017-03-21 Zoltan Buczolich

We study the complexity of approximate representation and learning of submodular functions over the uniform distribution on the Boolean hypercube $\{0,1\}^n$. Our main result is the following structural theorem: any submodular function is…

Machine Learning · Computer Science 2013-04-03 Vitaly Feldman , Pravesh Kothari , Jan Vondrak