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The vector space of all polynomial functions of degree $k$ on a box of dimension $n$ is of dimension ${n \choose k}$. A consequence of this fact is that a function can be approximated on vertices of the box using other vertices to higher…

Classical Analysis and ODEs · Mathematics 2018-05-10 Avichai Tendler , Uri Alon

Normal multi-scale transform [4] is a nonlinear multi-scale transform for representing geometric objects that has been recently investigated [1, 7, 10]. The restrictive role of the exact order of polynomial reproduction $P_e$ of the…

Numerical Analysis · Mathematics 2013-11-19 Stanislav Harizanov

Estimation is the computational task of recovering a hidden parameter $x$ associated with a distribution $D_x$, given a measurement $y$ sampled from the distribution. High dimensional estimation problems arise naturally in statistics,…

Data Structures and Algorithms · Computer Science 2019-08-07 Prasad Raghavendra , Tselil Schramm , David Steurer

Convergence of operators acting on a given Hilbert space is an old and well studied topic in operator theory. The idea of introducing a related notion for operators acting on arying spaces is natural. However, it seems that the first…

Functional Analysis · Mathematics 2014-01-17 Delio Mugnolo , Robin Nittka , Olaf Post

The calculation of a large family of four point functions of general BPS operators in N=4 SYM is reduced to the evaluation of colour contractions. For 1/2 BPS operators O_\Delta the explicit results at order g^4 for the function < O_n O_2…

High Energy Physics - Theory · Physics 2015-06-26 Marco D'Alessandro , Luigi Genovese

In this paper, we design high order accurate and stable finite difference schemes for the initial-boundary value problem, associated with the magnetic induction equation with resistivity. We use Summation-By-Parts (SBP) finite difference…

Analysis of PDEs · Mathematics 2011-02-03 U. Koley , S. Mishra , N. H. Risebro , And M. Svard

Efficiency of intrinsic operator techniques (using only products and ranks of tensor operators) is first evidenced by condensed proofs of already known $\bigtriangledown$-triangle sum rules of su(2)/su$_q$(2). {\em A new compact}…

Mathematical Physics · Physics 2008-11-14 Lionel Bréhamet

In this paper, we present a block-oriented scheme for adaptive mesh refinement based on summation-by-parts (SBP) finite difference methods and simultaneous-approximation-term (SAT) interface treatment. Since the order of accuracy at SBP-SAT…

Numerical Analysis · Mathematics 2019-03-05 Anna Nissen , Katharina Kormann , Magnus Grandin , Kristoffer Virta

We study the properties of different type of transforms by means of operational methods and discuss the relevant interplay with many families of special functions. We consider in particular the binomial transform and its generalizations. A…

Mathematical Physics · Physics 2010-10-11 G. Dattoli , E. Sabia

This is a survey on best polynomial approximation on the unit sphere and the unit ball. The central problem is to describe the approximation behavior of a function by polynomials via smoothness of the function. A major effort is to identify…

Classical Analysis and ODEs · Mathematics 2014-02-25 Yuan Xu

In the last decades many authors have become interested in the study of multilinear and polynomial generalizations of families of operator ideals (such as, for instance, the ideal of absolutely summing operators). However, these…

Submodular functions are at the core of many machine learning and data mining tasks. The underlying submodular functions for many of these tasks are decomposable, i.e., they are sum of several simple submodular functions. In many data…

Data Structures and Algorithms · Computer Science 2022-01-20 Akbar Rafiey , Yuichi Yoshida

We show that the binomial states (BS) of Stoler {\it et al.} admit the ladder and displacement operator formalism. By generalizing the ladder operator formalism we propose an eigenvalue equation which possesses the number and the squeezed…

Quantum Physics · Physics 2008-11-26 Hong-Chen Fu , Ryu Sasaki

Sampling-based algorithms are classical approaches to perform Bayesian inference in inverse problems. They provide estimators with the associated credibility intervals to quantify the uncertainty on the estimators. Although these methods…

Methodology · Statistics 2023-11-28 Pierre-Antoine Thouvenin , Audrey Repetti , Pierre Chainais

It is well-known that any sum of squares (SOS) program can be cast as a semidefinite program (SDP) of a particular structure and that therein lies the computational bottleneck for SOS programs, as the SDPs generated by this procedure are…

Optimization and Control · Mathematics 2017-10-05 Amir Ali Ahmadi , Georgina Hall , Antonis Papachristodoulou , James Saunderson , Yang Zheng

We will show that a local space-time estimate implies a global space-time estimate for dispersive operators. In order for this implication we consider a Littlewood-Paley type square function estimate for dispersive operators in a time…

Analysis of PDEs · Mathematics 2021-09-02 Chu-hee Cho , Youngwoo Koh , Jungjin Lee

The convergence of a new general variable metric algorithm based on compositions of averaged operators is established. Applications to monotone operator splitting are presented.

Optimization and Control · Mathematics 2018-07-12 Lilian E. Glaudin

This paper introduces a more restrictive notion of feasibility of functionals on Baire space than the established one from second-order complexity theory. Thereby making it possible to consider functions on the natural numbers as running…

Computational Complexity · Computer Science 2017-06-02 Akitoshi Kawamura , Florian Steinberg

In this paper, we present the basic concepts of the geometric theory of composition operators on Sobolev spaces. The main objects of the theory are topological mappings which generate bounded embedding operators on Sobolev spaces by the…

Analysis of PDEs · Mathematics 2024-11-21 Vladimir Gol'dshtein , Alexander Ukhlov

A sum-product network (SPN) is a probabilistic model, based on a rooted acyclic directed graph, in which terminal nodes represent univariate probability distributions and non-terminal nodes represent convex combinations (weighted sums) and…

Machine Learning · Computer Science 2020-04-03 Iago París , Raquel Sánchez-Cauce , Francisco Javier Díez