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We study generalized solutions of an evolutionary equation related to a densely defined skew-symmetric operator in a real Hilbert space. We establish existence of a contractive semigroup, which provides generalized solutions, and find…

Analysis of PDEs · Mathematics 2025-11-05 Evgeny Yu. Panov

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

We study the convergence of a random iterative sequence of a family of operators on infinite dimensional Hilbert spaces, inspired by the Stochastic Gradient Descent (SGD) algorithm in the case of the noiseless regression, as studied in [1].…

Functional Analysis · Mathematics 2022-09-02 Soumyadip Ghosh , Yingdong Lu , Tomasz J. Nowicki

We introduce a comprehensive framework for analyzing convergence rates for infinite dimensional linear programming problems (LPs) within the context of the moment-sum-of-squares hierarchy. Our primary focus is on extending the existing…

Optimization and Control · Mathematics 2025-05-09 Corbinian Schlosser , Matteo Tacchi , Alexey Lazarev

We discuss notions of Gauss curvature and mean curvature for polyhedral surfaces. The discretizations are guided by the principle of preserving integral relations for curvatures, like the Gauss/Bonnet theorem and the mean-curvature force…

Differential Geometry · Mathematics 2007-10-25 John M. Sullivan

Fractional derivatives are a well-studied generalization of integer order derivatives. Naturally, for optimization, it is of interest to understand the convergence properties of gradient descent using fractional derivatives. Convergence…

Optimization and Control · Mathematics 2024-06-05 Ashwani Aggarwal

In the last several years, the intimate connection between convex optimization and learning problems, in both statistical and sequential frameworks, has shifted the focus of algorithmic machine learning to examine this interplay. In…

Machine Learning · Computer Science 2014-07-23 Mehrdad Mahdavi

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

We prove global convergence of classical projection algorithms for feasibility problems involving union convex sets, which refer to sets expressible as the union of a finite number of closed convex sets. We present a unified strategy for…

Optimization and Control · Mathematics 2023-07-18 Jan Harold Alcantara , Ching-pei Lee

We show sharp square function estimates for curves in the plane whose curvature degenerates at a point and estimates sharp up to endpoints for cones over these curves. To this end, for curves of finite type we extend the classical…

Classical Analysis and ODEs · Mathematics 2024-08-15 Robert Schippa

Given a bounded Lipschitz domain $D\subset \mathbb{R}^d$ and a Calder\'on-Zygmund operator $T$, we study the relations between smoothness properties of $\partial D$ and the boundedness of $T$ on the Zydmund space $\mathcal{C}_{\omega}(D)$…

Functional Analysis · Mathematics 2023-09-25 Andrei V. Vasin

The generalized conditional gradient method is a popular algorithm for solving composite problems whose objective function is the sum of a smooth function and a nonsmooth convex function. Many convergence analyses of the algorithm rely on…

Optimization and Control · Mathematics 2025-05-05 Shotaro Yagishita

For a functional $\E$ and a peak selection that picks up a global maximum of $\E$ on varying cones, we study the convergence up to a subsequence to a critical point of the sequence generated by a mountain pass type algorithm. Moreover, by…

Analysis of PDEs · Mathematics 2013-01-09 Christopher Grumiau , Christophe Troestler

We analyze the constant step size subgradient method on nonsmooth, nonconvex functions. We identify geometric assumptions on the objective function under which i) its domain admits a partition (stratification) into smooth manifolds (strata)…

Optimization and Control · Mathematics 2026-04-21 Evgenii Chzhen , Sholom Schechtman

For generalized KdV models with polynomial nonlinearity, we establish nonlinear smoothing property in $H^s$ for $s>\frac{1}{2}$. Such smoothing effect persists globally, provided that the $H^1$ norm does not blow up in finite time. More…

Analysis of PDEs · Mathematics 2020-01-27 Seungly Oh , Atanas G. Stefanov

We study the arithmetic (geometric) progressions in the $x$-coordinates of quadratic points on smooth projective planar curves defined over a number field $k$. Unless the curve is hyperelliptic, we prove that these progressions must be…

Number Theory · Mathematics 2020-10-07 Eslam Badr , Mohammad Sadek

Numerical solutions of differential equations are usually not smooth functions. However, they should resemble the smoothness of the corresponding real solutions in one way or another. In two of our recent papers, a kind of spacial…

Numerical Analysis · Mathematics 2012-07-13 Tong Sun

For functions in the Sobolev space $H^s$ and decreasing sequences $t_n\to 0$ we examine convergence almost everywhere of the generalized Schr\"odinger means on the real line, given by \[S^af(x,t_n)=\exp( it_n (-\partial_{xx})^{a/2})f(x);\]…

Classical Analysis and ODEs · Mathematics 2020-04-06 Evangelos Dimou , Andreas Seeger

Numerical methods for SDEs with irregular coefficients are intensively studied in the literature, with different types of irregularities usually being attacked separately. In this paper we combine two different types of irregularities:…

Numerical Analysis · Mathematics 2024-01-12 Kathrin Spendier , Michaela Szölgyenyi

We study stochastic gradient descent {\em without replacement} (\sgdwor) for smooth convex functions. \sgdwor is widely observed to converge faster than true \sgd where each sample is drawn independently {\em with replacement}…

Optimization and Control · Mathematics 2020-02-28 Prateek Jain , Dheeraj Nagaraj , Praneeth Netrapalli
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