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In this paper, we show the existence of non-trivial solutions to very general elliptic systems with critical non-linearities in the sense of embeddings in Orlicz-Sobolev spaces. This allows to consider non-linearities which do not have…

Analysis of PDEs · Mathematics 2025-03-20 Pablo Ochoa

Recent advances in large-margin classification of data residing in general metric spaces (rather than Hilbert spaces) enable classification under various natural metrics, such as string edit and earthmover distance. A general framework…

Machine Learning · Computer Science 2014-07-14 Lee-Ad Gottlieb , Aryeh Kontorovich , Robert Krauthgamer

We give an alternative proof of the general chain rule for functions of bounded variation ([ADM90]), which allows to compute the distributional differential of $\varphi\circ F$, where $\varphi\in \mathrm{LIP}(\mathbb{R}^m)$ and…

Functional Analysis · Mathematics 2023-07-13 Camillo Brena , Nicola Gigli

It was established in [8] that Lipschitz inf-compact functions are uniquely determined by their local slope and critical values. Compactness played a paramount role in this result, ensuring in particular the existence of critical points. We…

Optimization and Control · Mathematics 2023-08-30 Aris Daniilidis , Tri Minh Le , David Salas

In a decision-theoretic framework, the minimax lower bound provides the worst-case performance of estimators relative to a given class of statistical models. For parametric and semiparametric models, the H\'{a}jek--Le Cam local asymptotic…

Statistics Theory · Mathematics 2024-10-22 Kenta Takatsu , Arun Kumar Kuchibhotla

We establish a priori Lipschitz estimates for unbounded solutions of second-order Hamilton-Jacobi equations in R^N in presence of an Ornstein-Uhlenbeck drift. We generalize the results obtained by Fujita, Ishii \& Loreti (2006) in several…

Analysis of PDEs · Mathematics 2017-05-03 Emmanuel Chasseigne , Olivier Ley , Thi-Tuyen Nguyen

For a dynamical system, we study the set of points $\cal W$ whose orbit approximates any chosen point at certain specified rates. Our basic setting is that of left shift acting on topological Markov chains endowed with a local weak Gibbs…

Dynamical Systems · Mathematics 2016-06-09 María Victoria Melián Pérez

In 1994, M. M. Popov [On integrability in F-spaces, Studia Math. no 3, 205-220] showed that the fundamental theorem of calculus fails, in general, for functions mapping from a compact interval of the real line into the lp-spaces for 0<p<1,…

Functional Analysis · Mathematics 2013-08-29 Fernando Albiac , Jose L Ansorena

Recently, Brandt, Maus and Uitto [PODC'19] showed that, in a restricted setting, the dependency of the complexity of the distributed Lov\'asz Local Lemma (LLL) on the chosen LLL criterion exhibits a sharp threshold phenomenon: They proved…

Data Structures and Algorithms · Computer Science 2020-06-09 Sebastian Brandt , Christoph Grunau , Václav Rozhoň

In this paper, we establish a suitable version of the Hahn-Banach theorem within the framework of Colombeau spaces, a class of spaces used to model generalized functions. Our approach addresses the case where maps are defined…

Functional Analysis · Mathematics 2024-10-14 Djamel eddine Kebiche , Paolo Giordano

By the Hardy-Littlewood-Sobolev theorem the classical Riesz potential is bounded on Lebesgue spaces. E. Nakai and H. Sumitomo [16] extended that theorem to the Orlicz spaces. We introduce generalized potential operators on commutative…

Functional Analysis · Mathematics 2013-07-19 Mubariz G. Hajibayov

The Schwarz lemma for holomorphic maps between Hermitian manifolds is improved. New curvature constraints on the source and target manifolds are introduced and shown to be weaker than the Ricci and real bisectional curvature, respectively.…

Differential Geometry · Mathematics 2023-09-12 Kyle Broder , James Stanfield

The purpose of this paper is to extend the embedding theorem of Sobolev spaces involving general kernels and we provide a sharp critical exponent in these embeddings. As an application, solutions for equations driven by a general…

Analysis of PDEs · Mathematics 2014-04-07 Huyuan Chen , Hichem Hajaiej

Lipschitz one-dimensional constrained global optimization (GO) problems where both the objective function and constraints can be multiextremal and non-differentiable are considered in this paper. Problems, where the constraints are verified…

Optimization and Control · Mathematics 2011-07-27 Yaroslav D. Sergeyev , Dmitri E. Kvasov , Falah M. H. Khalaf

The present paper is devoted to possible generalizations of the classic Lagrange Mean Value Theorem. We consider a real-valued function of several variables that is only assumed to be continuous. The main concept is to replace the notion of…

Classical Analysis and ODEs · Mathematics 2024-01-08 Karolina Zając

We consider a composite optimization problem where the sum of a continuously differentiable and a merely lower semicontinuous function has to be minimized. The proximal gradient algorithm is the classical method for solving such a problem…

Optimization and Control · Mathematics 2023-05-01 Xiaoxi Jia , Christian Kanzow , Patrick Mehlitz

In this paper we address the question of the existence of a spectral gap in a class of local Hamiltonians. These Hamiltonians have the following properties: their ground states are known exactly; all equal-time correlation functions of…

Strongly Correlated Electrons · Physics 2008-11-27 Michael Freedman , Chetan Nayak , Kirill Shtengel

An old result by Shearer relates the Lov\'asz Local Lemma with the independent set polynomial on graphs, and consequently, as observed by Scott and Sokal, with the partition function of the hard core lattice gas on graphs. We use this…

Combinatorics · Mathematics 2010-03-29 Rodrigo Bissacot , Roberto Fernández , Aldo Procacci , Benedetto Scoppola

Hybrid classical-quantum systems are of interest in numerous fields, from quantum chemistry to quantum information science. A fully quantum effective description of them is straightforward to formulate when the classical subsystem is…

Quantum Physics · Physics 2025-01-06 S. Camalet

Hamiltonian Monte Carlo (HMC) is a widely deployed method to sample from high-dimensional distributions in Statistics and Machine learning. HMC is known to run very efficiently in practice and its popular second-order "leapfrog"…

Data Structures and Algorithms · Computer Science 2018-08-13 Oren Mangoubi , Nisheeth K. Vishnoi