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This paper concerns quasi-stochastic approximation (QSA) to solve root finding problems commonly found in applications to optimization and reinforcement learning. The general constant gain algorithm may be expressed as the…

Optimization and Control · Mathematics 2024-04-02 Caio Kalil Lauand , Sean Meyn

In this work, we study the socially fair $k$-median/$k$-means problem. We are given a set of points $P$ in a metric space $\mathcal{X}$ with a distance function $d(.,.)$. There are $\ell$ groups: $P_1,\dotsc,P_{\ell} \subseteq P$. We are…

Data Structures and Algorithms · Computer Science 2021-09-14 Dishant Goyal , Ragesh Jaiswal

Nowadays, frequent pattern mining (FPM) on large graphs receives increasing attention, since it is crucial to a variety of applications, e.g., social analysis. Informally, the FPM problem is defined as finding all the patterns in a large…

Databases · Computer Science 2022-05-04 Xin Wang , Zhuo Lan , Yu-Ang He , Yang Wang , Zhi-Gui Liu , Wen-Bo Xie

Model approximations are common practice when estimating structural or quasi-structural models. The paper considers the econometric properties of estimators that utilize projections to reimpose information about the exact model in the form…

Econometrics · Economics 2024-03-05 Andreas Tryphonides

We investigate the fine-grained complexity of approximating the classical $k$-median / $k$-means clustering problems in general metric spaces. We show how to improve the approximation factors to $(1+2/e+\varepsilon)$ and…

Data Structures and Algorithms · Computer Science 2019-04-30 Vincent Cohen-Addad , Anupam Gupta , Amit Kumar , Euiwoong Lee , Jason Li

Let $\tau_k$ be the $k$-fold divisor function. By constructing an approximant of $\tau_k$, denoted as $\tau_k^*$, which is a normalized truncation of the $k$-fold divisor function, we prove that when $\exp\left(C\log^{1/2}X(\log\log…

Number Theory · Mathematics 2024-07-09 Mengdi Wang

The Metric $k$-median problem over a metric space $(\mathcal{X}, d)$ is defined as follows: given a set $L \subseteq \mathcal{X}$ of facility locations and a set $C \subseteq \mathcal{X}$ of clients, open a set $F \subseteq L$ of $k$…

Data Structures and Algorithms · Computer Science 2020-07-24 Dishant Goyal , Ragesh Jaiswal , Amit Kumar

We study the convergence of these operators in a weighted space of functions on a positive semi-axis and estimate the approximation by using a new type of weighted modulus of continuity and error estimation.

Classical Analysis and ODEs · Mathematics 2016-06-22 Preeti Sharma , Vishnu Narayan Mishra

Several questions of approximation theory are discussed: 1) can one approximate stably in $L^\infty$ norm $f^\prime$ given approximation $f_\delta, \parallel f_\delta - f \parallel_{L^\infty} < \delta$, of an unknown smooth function $f(x)$,…

Classical Analysis and ODEs · Mathematics 2007-05-23 A. G. Ramm

In this work we consider sums of primes that converging very slow. We set as a base, a reformulation of analytic prime number theorem and we use the values of Riemann Zeta function for the approximation. We also give the truncation error of…

Number Theory · Mathematics 2009-03-30 Nikos Bagis

We propose an approach to compute inner and outer-approximations of the sets of values satisfying constraints expressed as arbitrarily quantified formulas. Such formulas arise for instance when specifying important problems in control such…

Systems and Control · Electrical Eng. & Systems 2023-09-22 Eric Goubault , Sylvie Putot

For arbitrary $n$ complex numbers $a_{\nu-1}$, $\nu=1,\dots,n$, where $n$ is sufficiently large, we get the representation in the form of power sums: $a_{\nu-1}=\lambda_1^\nu+\dots+\lambda_{2n+1}^\nu$, where $\lambda_k$ are distinct points,…

Classical Analysis and ODEs · Mathematics 2018-07-18 Mikhail A. Komarov

The aim of this work is to introduced the concept of the best one-sided approximation of unbounded functions in weighted space by using algebraic operators in terms the average modulus of smoothness. We also show an estimate of the degree…

General Mathematics · Mathematics 2023-12-15 Raheam A. Al-Saphory , Abdullah A. Al-Hayani , Alaa A. Auad

In this work, we study a range of constrained versions of the $k$-supplier and $k$-center problems such as: capacitated, fault-tolerant, fair, etc. These problems fall under a broad framework of constrained clustering. A unified framework…

Data Structures and Algorithms · Computer Science 2021-10-28 Dishant Goyal , Ragesh Jaiswal

In this paper, we discuss numerical methods for the eigenvalue decomposition of real symmetric matrices. While many existing methods can compute approximate eigenpairs with sufficiently small backward errors, the magnitude of the resulting…

Numerical Analysis · Mathematics 2026-02-24 Takeshi Terao , Katsuhisa Ozaki

A $d$-{\em interval} is a union of at most $d$ disjoint closed intervals on a fixed line. Tardos [Combinatorica 15 (1995), 123-134] and the second author [Disc. Comput. Geom. 18 (1997), 195-203] used topological tools to bound the…

Combinatorics · Mathematics 2014-03-04 Ron Aharoni , Tomas Kaiser , Shira Zerbib

This paper provides intuition on the relationship of accrual and mark-to-market valuation for cash and forward interest rate trades. Discounted cashflow valuation is compared to spread-based valuation for forward trades, which explains the…

Pricing of Securities · Quantitative Finance 2016-02-22 Alexey Bakshaev

The Fourier transform is approximated over a finite domain using a Riemann sum. This Riemann sum is then expressed in terms of the discrete Fourier transform, which allows the sum to be computed with a fast Fourier transform algorithm more…

Numerical Analysis · Mathematics 2015-08-07 Jeremy Axelrod

We propose a focused weighted-average least squares (FWALS) estimator that addresses the computational burden of focused model averaging. By semi-orthogonalizing auxiliary regressors, the weighting problem is reduced from $2^{k_2}$…

Econometrics · Economics 2026-03-04 Shou-Yung Yin

Abundant literature has been published on approximation methods for the forward initial margin. The most popular ones being the family of regression methods. This paper describes the mathematical foundations on which these regression…

Risk Management · Quantitative Finance 2022-09-30 Lucia Cipolina Kun , Simone Caenazzo , Ksenia Ponomareva
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