English
Related papers

Related papers: On Symmetric Pseudo-Boolean Functions: Factorizati…

200 papers

We define an abelian group homomorphism $\mathscr{F}$, which we call the Frobenius transform, from the ring of symmetric functions to the ring of the symmetric power series. The matrix entries of $\mathscr{F}$ in the Schur basis are the…

Combinatorics · Mathematics 2024-06-27 Mitchell Lee

Interpolation and approximation of functionals with conditionally positive definite kernels is considered on sets of centers that are not determining for polynomials. It is shown that polynomial consistency is sufficient in order to define…

Numerical Analysis · Mathematics 2025-08-26 Oleg Davydov

Rotation symmetric Boolean functions represent an interesting class of Boolean functions as they are relatively rare compared to general Boolean functions. At the same time, the functions in this class can have excellent properties, making…

Neural and Evolutionary Computing · Computer Science 2023-11-21 Claude Carlet , Marko Ðurasevic , Bruno Gašperov , Domagoj Jakobovic , Luca Mariot , Stjepan Picek

We provide a holomorphic description of the Hilbert space H(j_1,..,j_n) of SU(2)-invariant tensors (intertwiners) and establish a holomorphically factorized formula for the decomposition of identity in H(j_1,..,j_n). Interestingly, the…

High Energy Physics - Theory · Physics 2015-03-13 Laurent Freidel , Kirill Krasnov , Etera R. Livine

The spectral norm of a Boolean function $f:\{0,1\}^n \to \{-1,1\}$ is the sum of the absolute values of its Fourier coefficients. This quantity provides useful upper and lower bounds on the complexity of a function in areas such as learning…

Computational Complexity · Computer Science 2012-05-25 Anil Ada , Omar Fawzi , Hamed Hatami

We present the SpinParser open-source software [ https://github.com/fbuessen/SpinParser ]. The software is designed to perform pseudofermion functional renormalization group (pf-FRG) calculations for frustrated quantum magnets in two and…

Computational Physics · Physics 2022-09-02 Finn Lasse Buessen

For the past 30 years or so, machine learning has stimulated a great deal of research in the study of approximation capabilities (expressive power) of a multitude of processes, such as approximation by shallow or deep neural networks,…

Machine Learning · Computer Science 2025-01-07 Hrushikesh Mhaskar

The relationship between quantum physics and discrete mathematics is reviewed in this article. The Boolean functions unitary representation is considered. The relationship between Zhegalkin polynomial, which defines the algebraic normal…

Quantum Physics · Physics 2019-06-18 Yu. I. Bogdanov , N. A. Bogdanova , D. V. Fastovets , V. F. Lukichev

Mapping functions on bits to Hamiltonians acting on qubits has many applications in quantum computing. In particular, Hamiltonians representing Boolean functions are required for applications of quantum annealing or the quantum approximate…

Quantum Physics · Physics 2021-12-30 Stuart Hadfield

We study the polynomial approximation of symmetric multivariate functions and of multi-set functions. Specifically, we consider $f(x_1, \dots, x_N)$, where $x_i \in \mathbb{R}^d$, and $f$ is invariant under permutations of its $N$…

Numerical Analysis · Mathematics 2023-02-06 Markus Bachmayr , Geneviève Dusson , Christoph Ortner , Jack Thomas

We consider certain scalar product of symmetric functions which is parameterized by a function $r$ and an integer $n$. One the one hand we have a fermionic representation of this scalar product. On the other hand we get a representation of…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 A. Yu. Orlov

We describe a method to perform functional operations on probability distributions of random variables. The method uses reproducing kernel Hilbert space representations of probability distributions, and it is applicable to all operations…

Machine Learning · Statistics 2016-09-14 Bernhard Schölkopf , Krikamol Muandet , Kenji Fukumizu , Jonas Peters

We address the problem of finding optimal strategies for computing Boolean symmetric functions. We consider a collocated network, where each node's transmissions can be heard by every other node. Each node has a Boolean measurement and we…

Information Theory · Computer Science 2009-11-18 Hemant Kowshik , P. R. Kumar

Computational asymmetry, i.e., the discrepancy between the complexity of transformations and the complexity of their inverses, is at the core of one-way transformations. We introduce a computational asymmetry function that measures the…

Group Theory · Mathematics 2007-05-23 Jean-Camille Birget

It is well known that over an infinite field the ring of symmetric functions in a finite number of variables is isomorphic to the one of polynomial functions on matrices that are invariants by the action of conjugation by general linear…

Combinatorics · Mathematics 2007-05-23 F. Vaccarino

We consider the problem of learning regression functions from pairwise data when there exists prior knowledge that the relation to be learned is symmetric or anti-symmetric. Such prior knowledge is commonly enforced by symmetrizing or…

Machine Learning · Computer Science 2015-06-22 Tapio Pahikkala , Markus Viljanen , Antti Airola , Willem Waegeman

Pseudo-splines form a family of subdivision schemes that provide a natural blend between interpolating schemes and approximating schemes, including the Dubuc-Deslauriers schemes and B-spline schemes. Using a generating function approach, we…

Numerical Analysis · Mathematics 2017-09-22 Georg Muntingh

The concept of rotation symmetric functions from the Boolean domain is extended to the multiple-valued (MV) domain. It is shown that symmetric functions are a subset of the rotation symmetric functions. Functions exhibiting these kinds of…

Combinatorics · Mathematics 2020-10-06 Claudio Moraga

Considering the kernel of an integral operator intertwining two realizations of the group of motions of the pseudo-Euclidian space, we derive two formulas for series containing Whittaker's functions or Weber's parabolic cylinder functions.…

Classical Analysis and ODEs · Mathematics 2023-06-22 J. Choi , I. A. Shilin

We consider the problem of representing Boolean functions exactly by "sparse" linear combinations (over $\mathbb{R}$) of functions from some "simple" class ${\cal C}$. In particular, given ${\cal C}$ we are interested in finding…

Computational Complexity · Computer Science 2018-02-27 R. Ryan Williams