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It is well-known since the work of Pardoux and Peng [12] that Backward Stochastic Differential Equations provide probabilistic formulae for the solution of (systems of) second order elliptic and parabolic equations, thus providing an…

Probability · Mathematics 2020-03-10 Etienne Pardoux , Aurel Rascanu

We study nonparametric Bayesian models for reversible multi-dimensional diffusions with periodic drift. For continuous observation paths, reversibility is exploited to prove a general posterior contraction rate theorem for the drift…

Statistics Theory · Mathematics 2024-08-02 Matteo Giordano , Kolyan Ray

We consider the large deviations associated with the empirical mean of independent and identically distributed random variables under a subexponential moment condition. We show that non-trivial deviations are observable at a subexponential…

Probability · Mathematics 2025-07-22 Grégoire Ferré

The popular BFGS quasi-Newton minimization algorithm under reasonable conditions converges globally on smooth convex functions. This result was proved by Powell in 1976: we consider its implications for functions that are not smooth. In…

Optimization and Control · Mathematics 2017-03-21 Jiayi Guo , Adrian Lewis

In this paper, we study the Liouville--type theorems for three--dimensional stationary incompressible MHD and Hall--MHD systems in a slab with periodic boundary condition. We show that, under the assumptions that $(u^\theta,b^\theta)$ or…

Analysis of PDEs · Mathematics 2022-12-13 Wentao Hu , Zhengce Zhang

This paper studies the convexity properties of nonsmooth extended-real-valued weakly convex functions, a class of functions that is central to modern optimization and its applications. We establish new characterizations of convexity using…

Optimization and Control · Mathematics 2026-03-27 Vo Thanh Phat

Gradient algorithms are classical in adaptive control and parameter estimation. For instantaneous quadratic cost functions they lead to a linear time-varying dynamic system that converges exponentially under persistence of excitation…

Optimization and Control · Mathematics 2020-10-06 Juan G. Rueda-Escobedo , Jaime A. Moreno

We prove that the Tate, Beilinson and Parshin conjectures are invariant under Homological Projective Duality (=HPD). As an application, we obtain a proof of these celebrated conjectures (as well as of the strong form of the Tate conjecture)…

Algebraic Geometry · Mathematics 2018-05-07 Goncalo Tabuada

In the early 1960's, Moreau and Rockafellar introduced a concept of called \emph{subgradient} for convex functions, initiating the developments of theoretical and applied convex analysis. The needs of going beyond convexity motivated the…

Optimization and Control · Mathematics 2013-08-06 Nguyen Mau Nam , Nguyen Dinh Hoang , R. Blake Rector

This paper is devoted to studying the first-order variational analysis of non-convex and non-differentiable functions that may not be subdifferentially regular. To achieve this goal, we entirely rely on two concepts of directional…

Optimization and Control · Mathematics 2022-04-22 Ashkan Mohammadi

In this work we obtain a Liouville theorem for positive, bounded solutions of the equation $$ (-\Delta)^s u= h(x_N)f(u) \quad \hbox{in }\mathbb{R}^{N} $$ where $(-\Delta)^s$ stands for the fractional Laplacian with $s\in (0,1)$, and the…

Analysis of PDEs · Mathematics 2017-09-25 B. Barrios , L. Del Pezzo , J. Garcia-Melian , A. Quaas

We prove Banach, Newton-Raphson and Brouwer fixed point theorems in the framework of generalized smooth functions, a minimal extension of Colombeau's theory (and hence of classical distribution theory) which makes it possible to model…

Functional Analysis · Mathematics 2026-03-10 Kevin Islami , George Apaaboah , Paolo Giordano

We prove that, for asymptotically bounded holomorphic functions in a sector in $\mathbb{C}$, an asymptotic expansion in a single direction towards the vertex with constraints in terms of a logarithmically convex sequence admitting a nonzero…

Complex Variables · Mathematics 2022-12-29 Javier Jiménez-Garrido , Javier Sanz , Gerhard Schindl

In this research article, we formulate and prove multidimensional Widder--Arendt theorem and integrated form of multidimensional Widder--Arendt theorem for functions with values in sequentially complete locally convex spaces. Established…

Functional Analysis · Mathematics 2025-11-25 Marko Kostic

Brouwer's fixed point theorem states that any continuous function from a closed $n$-dimensional ball to itself has a fixed point. In 1961, Klee showed that if such a function has discontinuities that are bounded, then it has a point that is…

Metric Geometry · Mathematics 2025-12-18 Henry Adams , Florian Frick

In this work, it is presented an adaptation of an asymptotic theorem of N. Levinson of 1948, to differential equation with piecewise constant argument generalized, which were introduced by M. Akhmet in 2007. By simplicity and without loss…

Classical Analysis and ODEs · Mathematics 2015-05-21 Samuel Castillo , Wilfred Flores

We consider the Cahn-Hilliard equation in one space dimension with scaling a small parameter \epsilon and a non-convex potential W. In the limit \espilon \to 0, under the assumption that the initial data are energetically well-prepared, we…

Analysis of PDEs · Mathematics 2012-02-09 Giovanni Bellettini , Lorenzo Bertini , Mauro Mariani , Matteo Novaga

We consider the elliptic equation $-\Delta u = u^q|\nabla u|^p$ in $\mathbb R^n$ for any $p\ge 2$ and $q>0$. We prove a Liouville-type theorem, which asserts that any positive bounded solution is constant. The proof technique is based on…

Analysis of PDEs · Mathematics 2025-04-30 Roberta Filippucci , Patrizia Pucci , Philippe Souplet

Michael Handel proved in [7] the existence of a fixed point for an orientation preserving homeomorphism of the open unit disk that can be extended to the closed disk, provided that it has points whose orbits form an oriented cycle of links…

Dynamical Systems · Mathematics 2012-08-13 Juliana Xavier

Motivated by a wide variety of applications, ranging from stochastic optimization to dimension reduction through variable selection, the problem of estimating gradients accurately is of crucial importance in statistics and learning theory.…

Machine Learning · Computer Science 2020-06-29 Guillaume Ausset , Stephan Clémençon , François Portier