Results 41 to 50 of about 1,527,957 (300)

Deterministic polynomial-time approximation algorithms for partition functions and graph polynomials [PDF]

open access: yesElectron. Notes Discret. Math., 2016
We show a new way of constructing deterministic polynomial-time approximation algorithms for computing complex-valued evaluations of a large class of graph polynomials on bounded degree graphs.
Viresh Patel, Guus Regts
semanticscholar   +1 more source

Minimax Rates of Entropy Estimation on Large Alphabets via Best Polynomial Approximation [PDF]

open access: yesIEEE Transactions on Information Theory, 2014
Consider the problem of estimating the Shannon entropy of a distribution over k elements from n independent samples. We show that the minimax mean-square error is within the universal multiplicative constant factors of (k/n log k)2 t log2 k/n if n ...
Yihong Wu, Pengkun Yang
semanticscholar   +1 more source

Approximation by homogeneous polynomials [PDF]

open access: yesJournal of Approximation Theory, 2013
Uniform approximations by even degree homogeneous polynomials are considered. For a centrally symmetric convex set with nonempty interior, all even continuous functions on its boundary (in two space dimensions; the problem is open for higher dimensions) can be uniformly approximated by them. This is a new, more elementary proof of this fact.
openaire   +3 more sources

The best uniform quadratic approximation of circular arcs with high accuracy

open access: yesOpen Mathematics, 2016
In this article, the issue of the best uniform approximation of circular arcs with parametrically defined polynomial curves is considered. The best uniform approximation of degree 2 to a circular arc is given in explicit form.
Rababah Abedallah
doaj   +1 more source

A method for increasing the order of approximation to an arbitrary natural number by the numerical integration of boundary value problems for inhomogeneous linear ordinary differential equations of various degrees with variable coefficients by the matrix method

open access: yesVestnik Samarskogo Gosudarstvennogo Tehničeskogo Universiteta. Seriâ: Fiziko-Matematičeskie Nauki, 2020
The paper includes the well-known matrix method of numerical integration of boundary value problems for inhomogeneous linear ordinary differential equations with variable coefficients, which provides retaining an arbitrary number of Taylor series ...
Vladimir Nikolaevich Maklakov
doaj   +1 more source

Sparse polynomial approximation of parametric elliptic PDEs. Part II: lognormal coefficients [PDF]

open access: yes, 2015
Elliptic partial differential equations with diffusion coefficients of lognormal form, that is $a=exp(b)$, where $b$ is a Gaussian random field, are considered.
M. Bachmayr   +3 more
semanticscholar   +1 more source

Approximating a Norm by a Polynomial [PDF]

open access: yes, 2003
We prove that for any norm |*| in the d-dimensional real vector space V and for any odd n>0 there is a non-negative polynomial p(x), x in V of degree 2n such that p^{1/2n}(x) < |x| < c(n,d) p^{1/2n}(x), where c(n,d)={n+d-1 choose n}^{1/2n}. Corollaries and polynomial approximations of the Minkowski functional of a convex body are discussed.
openaire   +2 more sources

On the Approximation of the Jacobi Polynomials

open access: yesRocky Mountain Journal of Mathematics, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Elias, Uri, Gingold, Harry
openaire   +3 more sources

A Polynomial Quantum Algorithm for Approximating the Jones Polynomial [PDF]

open access: yesAlgorithmica, 2006
The Jones polynomial, discovered in 1984, is an important knot invariant in topology. Among its many connections to various mathematical and physical areas, it is known (due to Witten) to be intimately connected to Topological Quantum Field Theory (TQFT).
Dorit Aharonov   +2 more
openaire   +3 more sources

Provably Efficient Reinforcement Learning with Linear Function Approximation [PDF]

open access: yesAnnual Conference Computational Learning Theory, 2019
Modern reinforcement learning (RL) is commonly applied to practical problems with an enormous number of states, where function approximation must be deployed to approximate either the value function or the policy.
Chi Jin   +3 more
semanticscholar   +1 more source

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