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Motivated by applications in optimization and machine learning, we consider stochastic quasi-Newton (SQN) methods for solving stochastic optimization problems. In the literature, the convergence analysis of these algorithms relies on strong…

Optimization and Control · Mathematics 2016-03-16 Farzad Yousefian , Angelia Nedić , Uday V. Shanbha

We introduce and study a family of integral operators in the Kantorovich sense for functions acting on locally compact topological groups. We obtain convergence results for the above operators with respect to the pointwise and uniform…

Functional Analysis · Mathematics 2014-08-26 Gianluca Vinti , Luca Zampogni

In this paper, we investigate the approximation properties of the summation-integral type operators as defined by Mishra et al. (Boll. Unione Mat. Ital. (2016) 8:297-305) and determine the local results as well as prove the convergence…

Functional Analysis · Mathematics 2020-02-25 Rishikesh Yadav , Ramakanta Meher , Vishnu Narayan Mishra

This paper studies a method, which has been proposed in the Physics literature by [8, 7, 10], for estimating the quasi-stationary distribution. In contrast to existing methods in eigenvector estimation, the method eliminates the need for…

Probability · Mathematics 2014-01-03 Jose Blanchet , Peter Glynn , Shuheng Zheng

We study the convergence of $Q$-learning with linear function approximation. Our key contribution is the introduction of a novel multi-Bellman operator that extends the traditional Bellman operator. By exploring the properties of this…

Machine Learning · Computer Science 2023-10-02 Diogo S. Carvalho , Pedro A. Santos , Francisco S. Melo

Operator learning has been highly successful for continuous mappings between infinite-dimensional spaces, such as PDE solution operators. However, many operators of interest-including differential operators-are discontinuous or set-valued,…

Machine Learning · Computer Science 2026-05-13 Takashi Furuya , Yury Korolev , Takaharu Yaguchi

Homogenization for non-local operators in periodic environments has been studied intensively. So far, these works are mainly devoted to the qualitative results, that is, to determine explicitly the operators in the limit. To the best of…

Analysis of PDEs · Mathematics 2024-09-13 Xin Chen , Zhen-Qing Chen , Takashi Kumagai , Jian Wang

Artificial neural network operators (ANNOs) have been widely used for approximating deterministic input-output functions; however, their extension to random dynamics remains comparatively unexplored. In this paper, we construct a new class…

Machine Learning · Computer Science 2026-01-08 Sachin Saini , Uaday Singh

The approximate representation of operators by finite matrices is analysed in terms of accuracy and convergence. The identity operator, for example, can be reconstructed using a basis of harmonic oscillator states leading to a narrow peak…

Mathematical Physics · Physics 2025-12-02 B. G. Giraud , S. Karataglidis , K. Murulane , R. Peschanski

In this article, the approximation properties of the Szasz-Mirakjan type operators are studied for the function of two variables, and the rate of convergence of the bivariate operators is determined in terms of total and partial modulus of…

Functional Analysis · Mathematics 2020-05-27 Rishikesh Yadav , Ramakanta Meher , Vishnu Narayan Mishra

The Bishop-Phelps-Bollob\'as property for operators deals with simultaneous approximation of an operator $T$ and a vector $x$ at which $T: X\rightarrow Y$ nearly attains its norm by an operator $F$ and a vector $z$, respectively, such that…

Functional Analysis · Mathematics 2017-04-25 Vladimir Kadets , Mariia Soloviova

We adapt the quasi-monotone method from [2] for composite convex minimization in the stochastic setting. For the proposed numerical scheme we derive the optimal convergence rate in terms of the last iterate, rather than on average as it is…

Optimization and Control · Mathematics 2021-07-09 Vyacheslav Kungurtsev , Vladimir Shikhman

In this paper, we establish a comprehensive characterization of the generalized Lipschitz classes through the study of the rate of convergence of a family of semi-discrete sampling operators, of Durrmeyer type, in $L^p$-setting. To achieve…

Functional Analysis · Mathematics 2025-11-14 Danilo Costarelli , Michele Piconi , Gianluca Vinti

This paper is aimed at studying sensitivity of parameters \alpha and \beta appearing in the operators introduced by D.D. Stancu [11] in 1969. Results are established on the behavior the nodes used in Bernstein-Stancu polynomials and the…

Classical Analysis and ODEs · Mathematics 2017-07-25 R. B. Gandhi , Vishnu Narayan Mishra

In the present article, we propose the new class positive linear operators, which discrete type depending on a real parameters. These operators are similar to Jain operators but its approximation properties are different then Jain…

Classical Analysis and ODEs · Mathematics 2019-04-19 Prashantkumar Patel

This survey on approximations of perturbed operator functions addresses recent advances and some of the successful methods.

Functional Analysis · Mathematics 2013-03-01 Anna Skripka

In this article we derive quantitative uniqueness and approximation properties for (perturbations) of Riesz transforms. Seeking to provide robust arguments, we adopt a PDE point of view and realize our operators as harmonic extensions,…

Analysis of PDEs · Mathematics 2017-08-16 Angkana Rüland

The convolution quadrature theory is a systematic approach to analyse the approximation of the Riemann-Liouville fractional operator $I^{\alpha}$ at node $x_{n}$. In this paper, we develop the shifted convolution quadrature ($SCQ$) theory…

Numerical Analysis · Mathematics 2019-08-09 Yang Liu , Baoli Yin , Hong Li , Zhimin Zhang

The purpose of this paper is to study the approximation of vector valued mappings defined on a subset of a normed space. We investigate Korovkin-type conditions under which a given sequence of linear operators becomes a so-called…

Functional Analysis · Mathematics 2007-05-23 Lorenzo D'Ambrosio

Truncating the Fourier transform averaged by means of a generalized Hausdorff operator, we approximate the adjoint to that Hausdorff operator of the given function. We find the formulas for the rate of approximation in various metrics in…

Classical Analysis and ODEs · Mathematics 2019-07-31 Alberto Debernardi , Elijah Liflyand
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