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Nisan and Szegedy (CC 1994) showed that any Boolean function $f:\{0,1\}^n\rightarrow \{0,1\}$ that depends on all its input variables, when represented as a real-valued multivariate polynomial $P(x_1,\ldots,x_n)$, has degree at least $\log…

Computational Complexity · Computer Science 2021-07-08 Srikanth Srinivasan , S. Venkitesh

The approximate degree of a Boolean function f is the least degree of a real polynomial that approximates f pointwise to error at most 1/3. Approximate degree is known to be a lower bound on quantum query complexity. We resolve or nearly…

Quantum Physics · Physics 2019-08-20 Mark Bun , Robin Kothari , Justin Thaler

Relations between the decision tree complexity and various other complexity measures of Boolean functions is a thriving topic of research in computational complexity. It is known that decision tree complexity is bounded above by the cube of…

Computational Complexity · Computer Science 2022-09-19 Rahul Chugh , Supartha Podder , Swagato Sanyal

Vapnik--Chervonenkis' theorem is a seminal result in machine learning. It establishes sufficient conditions for empirical probabilities to converge to theoretical probabilities, uniformly over families of events. It also provides an…

Machine Learning · Computer Science 2026-01-26 A. Iosevich , A. Vagharshakyan , E. Wyman

Sensitivity, block sensitivity and certificate complexity are basic complexity measures of Boolean functions. The famous sensitivity conjecture claims that sensitivity is polynomially related to block sensitivity. However, it has been…

Computational Complexity · Computer Science 2015-06-09 Andris Ambainis , Krišjānis Prūsis , Jevgēnijs Vihrovs

The fundamental theorem of statistical learning states that binary PAC learning is governed by a single parameter -- the Vapnik-Chervonenkis (VC) dimension -- which determines both learnability and sample complexity. Extending this to…

Machine Learning · Computer Science 2025-11-18 Alon Cohen , Liad Erez , Steve Hanneke , Tomer Koren , Yishay Mansour , Shay Moran , Qian Zhang

The concept of Vapnik-Chervonenkis (VC) density is pivotal across various mathematical fields, including discrete geometry, probability theory and model theory. In this paper, we introduce a topological generalization of VC-density. Let $Y$…

Logic · Mathematics 2025-06-04 Saugata Basu , Deepam Patel

The VC-dimension, introduced by Vapnik and Chervonenkis in 1968 in the context of learning theory, has in recent years provided a rich source of problems in combinatorial geometry. Given $E\subseteq \mathbb{F}_q^d$ or $E\subseteq…

Combinatorics · Mathematics 2025-11-24 Moustapha Diallo , Brian McDonald

We show various uncertainty principles for the Fourier transform on harmonic manifolds of rank one. In particular, we derive a Heisenberg uncertainty principle, a Morgen theorem, an uncertainty principle for the Schr\"odinger equation and a…

Differential Geometry · Mathematics 2024-08-30 Oliver Brammen

This study explores the cosmological constant problem and modified uncertainty principle within a unified framework inspired by a void-dominated scenario. In a recent paper~\cite{Yusofi:2022hgg}, voids were modeled as spherical bubbles of…

General Relativity and Quantum Cosmology · Physics 2024-05-14 S. Ahmadi , E. Yusofi , M. A. Ramzanpour

We generalize and extend the ideas in a recent paper of Chiarelli, Hatami and Saks to prove new bounds on the number of relevant variables for boolean functions in terms of a variety of complexity measures. Our approach unifies and refines…

Combinatorics · Mathematics 2022-12-23 Jake Wellens

We study a natural complexity measure of Boolean functions known as the rational degree. Denoted $\textrm{rdeg}(f)$, it is the minimal degree of a rational function that is equal to $f$ on the Boolean hypercube. For total functions $f$, it…

Computational Complexity · Computer Science 2025-04-16 Vishnu Iyer , Siddhartha Jain , Robin Kothari , Matt Kovacs-Deak , Vinayak M. Kumar , Luke Schaeffer , Daochen Wang , Michael Whitmeyer

Let f:{-1,1}^n -> R be a real function on the hypercube, given by its discrete Fourier expansion, or, equivalently, represented as a multilinear polynomial. We say that it is Boolean if its image is in {-1,1}. We show that every function on…

Discrete Mathematics · Computer Science 2013-11-13 Tom Gur , Omer Tamuz

We study generalized uncertainty principle through the basic concepts of limit and Fourier transformation and analyze both the quantum theory of gravity and string theory from the perspective of complex function theory. Motivated from the…

High Energy Physics - Theory · Physics 2011-09-22 Bhupendra Nath Tiwari

We initiate the study of a new model of query complexity of Boolean functions where, in addition to 0 and 1, the oracle can answer queries with ``unknown''. The query algorithm is expected to output the function value if it can be…

Computational Complexity · Computer Science 2024-12-10 Nikhil S. Mande , Karteek Sreenivasaiah

A classical theorem of Nisan and Szegedy says that a boolean function with degree $d$ as a real polynomial depends on at most $d2^{d-1}$ of its variables. In recent work by Chiarelli, Hatami and Saks, this upper bound was improved to $C…

Discrete Mathematics · Computer Science 2019-03-22 Jake Wellens

The aim of this article is to formulate some novel uncertainty principles for the continuous shearlet transforms in arbitrary space dimensions. Firstly, we derive an analogue of the Pitt's inequality for the continuous shearlet transforms,…

Functional Analysis · Mathematics 2019-06-05 Firdous A. Shah , Azhar Y. Tantary

In this paper, we consider bounded width circuits and nondeterministic circuits in three somewhat new directions. In the first part of this paper, we mainly consider bounded width circuits. The main purpose of this part is to prove that…

Computational Complexity · Computer Science 2019-04-15 Hiroki Morizumi

The disjointness problem - where Alice and Bob are given two subsets of $\{1, \dots, n\}$ and they have to check if their sets intersect - is a central problem in the world of communication complexity. While both deterministic and…

Computational Complexity · Computer Science 2020-06-25 Anup Bhattacharya , Sourav Chakraborty , Arijit Ghosh , Gopinath Mishra , Manaswi Paraashar

The classical uncertainty principle of harmonic analysis states that a nontrivial function and its Fourier transform cannot both be sharply localized. It plays an important role in signal processing and physics. This paper generalizes the…

Information Theory · Computer Science 2017-08-02 Kit Ian Kou , Yan Yang , Cuiming Zou