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Related papers: Hyperfinite Construction of $G$-expectation

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A high order expansion of the renewal function is provided under the assumption that the inter-renewal time distribution is light tailed with finite moment generating function g on a neighborhood of 0. This expansion relies on complex…

Probability · Mathematics 2016-11-29 Clément Dombry , Landy Rabehasaina

In recent work, the authors proved a general result on lifting $G$-irreducible odd Galois representations $\mathrm{Gal}(\overline{F}/F) \to G(\overline{\mathbb{F}}_{\ell})$, with $F$ a totally real number field and $G$ a reductive group, to…

Number Theory · Mathematics 2020-07-24 Najmuddin Fakhruddin , Chandrashekhar Khare , Stefan Patrikis

In this paper, we propose a class of discrete-time approximation schemes for stochastic optimal control problems under the $G$-expectation framework. The proposed schemes are constructed recursively based on piecewise constant policy. We…

Optimization and Control · Mathematics 2021-10-05 Lianzi Jiang

We define an infinite dimensional modification of lower-semicomputability of density operators by G\'acs with an attempt to fix some problem in the paper. Our attempt is partly achieved by showing the existence of universal operator under…

Information Theory · Computer Science 2016-02-22 Toru Takisaka

This commentary considers non-standard analysis and a recently introduced computational methodology based on the notion of \G1 (this symbol is called \emph{grossone}). The latter approach was developed with the intention to allow one to…

General Mathematics · Mathematics 2018-07-25 Yaroslav D. Sergeyev

We provide a general approach to construct a stochastic process with a given consistent family of finite dimensional distributions under a nonlinear expectation space. We use this approach to construct a generalized Gaussian process under a…

Probability · Mathematics 2011-05-06 Shige Peng

Geometric semigroup theory is the systematic investigation of finitely-generated semigroups using the topology and geometry of their associated automata. In this article we show how a number of easily-defined expansions on finite semigroups…

Group Theory · Mathematics 2011-04-13 Jon McCammond , John Rhodes , Benjamin Steinberg

We utilize an ergodic theory framework to explore sublinear expectation theory. Specifically, we investigate the pointwise Birkhoff's ergodic theorem for invariant sublinear expectation systems. By further assuming that these sublinear…

Probability · Mathematics 2024-12-03 Wen Huang , Chunlin Liu , Shige Peng , Baoyou Qu

In this paper, the Neyman-Pearson lemma for general sublinear expectations is studied. We weaken the assumptions for sublinear expectations in [1] and give a completely new method to study this problem. Applying Mazur-Orlicz Theorem and the…

Probability · Mathematics 2021-08-31 Chuanfeng Sun , Shaolin Ji

In this paper, we study the pricing of contingent claims under G-expectation. In order to accomodate volatility uncertainty, the price of the risky security is supposed to governed by a general linear stochastic differential equation (SDE)…

Probability · Mathematics 2013-03-19 Mingshang Hu , Shaolin Ji

We apply the topology of convergence on compact sets to define unpredictable functions [5, 6]. The topology is metrizable and easy for applications with integral operators. To demonstrate the effectiveness of the approach, the existence and…

Chaotic Dynamics · Physics 2016-11-17 Marat Akhmet , Mehmet Onur Fen

Geoffrion's theorem is a fundamental result from mathematical programming assessing the quality of Lagrangian relaxation, a standard technique to get bounds for integer programs. An often implicit condition is that the set of feasible…

Optimization and Control · Mathematics 2025-10-14 Santanu S. Dey , Frédéric Meunier , Diego Moran Ramirez

We consider coherent sublinear expectations on a measurable space, without assuming the existence of a dominating probability measure. By considering a decomposition of the space in terms of the supports of the measures representing our…

Probability · Mathematics 2011-10-27 Samuel N. Cohen

This paper develops a discontinuous Galerkin (DG) finite element differential calculus theory for approximating weak derivatives of Sobolev functions and piecewise Sobolev functions. By introducing numerical one-sided derivatives as…

Numerical Analysis · Mathematics 2013-03-06 Xiaobing Feng , Thomas Lewis , Michael Neilan

We derive a new class of non-linear expectations from first-principles deterministic chaotic dynamics. The homogenization of the system's skew-adjoint microscopic generator is achieved using the spectral theory of transfer operators for…

Probability · Mathematics 2025-12-02 Qian Qi

Let $G$ be a real classical group (including the real metaplectic group). We consider a nilpotent adjoint orbit $\check{\mathcal O}$ of $\check G$, the Langlands dual of $G$ (or the metaplectic dual of $G$ when $G$ is a real metaplectic…

Representation Theory · Mathematics 2025-02-19 Dan Barbasch , Jia-Jun Ma , Binyong Sun , Chen-Bo Zhu

A function $f$ on a topological space is sequentially continuous at a point $u$ if, given a sequence $(x_{n})$, $\lim x_{n}=u$ implies that $\lim f(x_{n})=f(u)$. This definition was modified by Connor and Grosse-Erdmann for real functions…

General Topology · Mathematics 2010-11-12 Huseyin Cakalli

This paper introduces the notion of pseudo-independence on the sublinear expectation space $(\Omega,\mathcal{F},\mathcal{P})$ via the classical conditional expectation, and the relations between pseudo-independence and Peng's independence…

Probability · Mathematics 2021-06-01 Xinpeng Li

Let $\varphi\colon\Gamma\to G$ be a homomorphism of groups. In this paper we introduce the notion of a subnormal map (the inclusion of a subnormal subgroup into a group being a basic prototype). We then consider factorizations…

Group Theory · Mathematics 2014-05-02 Emmanuel D. Farjoun , Yoav Segev

Gaussian process (GP) priors are non-parametric generative models with appealing modelling properties for Bayesian inference: they can model non-linear relationships through noisy observations, have closed-form expressions for training and…

Machine Learning · Statistics 2020-01-31 Gonzalo Rios
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