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Related papers: Minimizers of Convex Functionals Arising in Random…

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Minimizers of functionals of mixed local and nonlocal type are locally $C^{1,\beta}$-regular.

Analysis of PDEs · Mathematics 2022-05-03 Cristiana De Filippis , Giuseppe Mingione

In this short note we improve some of recent results of Cuckovic and Sahutoglu concerning regularity of the Berezin transform for a class of smooth pseudoconvex domains.

Functional Analysis · Mathematics 2020-07-28 Akaki Tikaradze

We show that the problem of tiling the Euclidean plane with a finite set of polygons (up to translation) boils down to prove the existence of zeros of a non-negative convex function defined on a finite-dimensional simplex. This function is…

Metric Geometry · Mathematics 2014-07-08 J. -R. Chazottes , J. -M. Gambaudo , F. Gautero

This paper tackles the unconstrained minimization of a class of nonsmooth and nonconvex functions that can be written as finite max-functions. A gradient and function-based sampling method is proposed which, under special circumstances,…

Optimization and Control · Mathematics 2019-04-03 Elias S. Helou , Sandra A. Santos , Lucas E. A. Simões

We study differentiable strongly quasiconvex functions for providing new properties for algorithmic and monotonicity purposes. Furthemore, we provide insights into the decreasing behaviour of strongly quasiconvex functions, applying this…

Optimization and Control · Mathematics 2024-10-07 Felipe Lara , Raúl T. Marcavillaca , Phan T. Vuong

We present a minimax optimal solution to the problem of estimating a compact, convex set from finitely many noisy measurements of its support function. The solution is based on appropriate regularizations of the least squares estimator.…

Statistics Theory · Mathematics 2012-05-31 Adityanand Guntuboyina

This paper introduces a smoothed proximal Lagrangian method for minimizing a nonconvex smooth function over a convex domain with additional explicit convex nonlinear constraints. Two key features are 1) the proposed method is single-looped,…

Optimization and Control · Mathematics 2024-08-28 Wenqiang Pu , Kaizhao Sun , Jiawei Zhang

We study a class of statistical inverse problems with non-linear pointwise operators motivated by concrete statistical applications. A two-step procedure is proposed, where the first step smoothes the data and inverts the non-linearity.…

Statistics Theory · Mathematics 2016-11-08 Kolyan Ray , Johannes Schmidt-Hieber

This work explores a novel perspective on solving nonconvex and nonsmooth optimization problems by leveraging sampling based methods. Instead of treating the objective function purely through traditional (often deterministic) optimization…

Optimization and Control · Mathematics 2025-05-21 Nahom Seyoum , Haoxiang You

We investigate the Hawking energy of small surfaces in space times without symmetry assumptions by introducing the notion of Hawking type functionals. In particular, we find that Hawking type functionals are generalized Willmore functionals…

Differential Geometry · Mathematics 2021-03-03 Alexander Friedrich

We consider the asymptotic behavior of properly embedded minimal surfaces in the product of the hyperbolic plane with the line, taking into account the fact that there is more than one natural compactification of this space. This provides a…

Differential Geometry · Mathematics 2015-06-10 Benoit Kloeckner , Rafe Mazzeo

Two criteria for the robust quasiconvexity of lower semicontinuous functions are established in terms of Fr\'echet subdifferentials in Asplund spaces.

Functional Analysis · Mathematics 2018-04-20 Hoa T. Bui , Pham Duy Khanh , Tran Thi Tu Trinh

Results on asymptotic characteristics of classes of functions with mixed smoothness are obtained in the paper. Our main interest is in estimating the Kolmogorov widths of classes with small mixed smoothness. We prove the corresponding…

Numerical Analysis · Mathematics 2020-12-21 V. Temlyakov , T. Ullrich

We establish the existence and smoothness of minimizers of the Willmore energy among axially symmetric surfaces of spherical type with prescribed isoperimetric ratio. Afterwards, we study the behavior of these minimizers as the…

Differential Geometry · Mathematics 2023-04-11 Jan-Henrik Metsch

We characterize the convexity of functions and the monotonicity of vector fields on metric measure spaces with Riemannian Ricci curvature bounded from below. Our result offers a new approach to deal with some rigidity theorems such as…

Functional Analysis · Mathematics 2021-08-17 Bang-Xian Han

In this paper some adaptive mirror descent algorithms for problems of minimization convex objective functional with several convex Lipschitz (generally, non-smooth) functional constraints are considered. It is shown that the methods are…

Optimization and Control · Mathematics 2018-12-20 F. S. Stonyakin , M . S. Alkousa , A. A. Titov

We discuss $(K,N)$-convexity and gradient flows for $(K,N)$-convex functionals on metric spaces, in the case of real $K$ and negative $N$. In this generality, it is necessary to consider functionals unbounded from below and/or above,…

Functional Analysis · Mathematics 2026-05-25 Lorenzo Dello Schiavo , Mattia Magnabosco , Chiara Rigoni

We revisit the problem of approximating minimizers of certain convex functionals subject to a convexity constraint by solutions of fourth order equations of Abreu type. This approximation problem was studied in previous works of…

Analysis of PDEs · Mathematics 2020-02-12 Nam Q. Le

Detecting hidden convexity is one of the tools to address nonconvex minimization problems. After giving a formal definition of hidden convexity, we introduce the notion of conditional infimum, as it will prove instrumental in detecting…

Optimization and Control · Mathematics 2021-04-13 Jean-Philippe Chancelier , Michel de Lara

We establish existence of steepest descent curves emanating from almost every point of a regular locally Lipschitz quasiconvex functions, where regularity means that the sweeping process flow induced by the sublevel sets is reversible. We…

Optimization and Control · Mathematics 2024-07-19 Aris Daniilidis , David Salas
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