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We propose a new stochastic gradient method for optimizing the sum of a finite set of smooth functions, where the sum is strongly convex. While standard stochastic gradient methods converge at sublinear rates for this problem, the proposed…

Optimization and Control · Mathematics 2013-03-12 Nicolas Le Roux , Mark Schmidt , Francis Bach

As an alternative to the well-known methods of "chaining" and "bracketing" that have been developed in the study of random fields, a new method, which is based on a {\em stochastic maximal inequality} derived by using the formula for…

Probability · Mathematics 2017-08-16 Yoichi Nishiyama

This topical review describes the methodology of continuum variational and diffusion quantum Monte Carlo calculations. These stochastic methods are based on many-body wave functions and are capable of achieving very high accuracy. The…

Materials Science · Physics 2010-02-11 R. J. Needs , M. D. Towler , N. D. Drummond , P. Lopez Rios

We develop a geometric version of the inverse problem of the calculus of variations for discrete mechanics and constrained discrete mechanics. The geometric approach consists of using suitable Lagrangian and isotropic submanifolds. We also…

Differential Geometry · Mathematics 2018-05-09 María Barbero-Liñán , Marta Farré Puiggalí , Sebastián Ferraro , David Martín de Diego

The main object of the present paper is to, introduce the. class of meromorphic univalent functions Involving! hypergeomatrc function .We obtain~ some interesting geometric properties according to coefficient inequality , growth and…

Complex Variables · Mathematics 2020-05-15 Mazin Sh. Mahmoud , Abdul Rahman S. Juma , Raheam A. Mansor Al-Saphory

Here we introduce some new classes of discrete stable random variables, which are useful for understanding of a new general notion of stability of random variables called us as casual stability. There are given some examples of casual and…

Probability · Mathematics 2014-06-17 Lev B. Klebanov , Lenka Slámová

In the present work, an attempted was made to develop a numerical algorithm by the use of new orthogonal hybrid functions formed from hybrid of piecewise constant orthogonal sample-and-hold functions and piecewise linear orthogonal…

Numerical Analysis · Mathematics 2018-01-23 Seshu Kumar Damarla , Madhusree Kundu

We define Bregman variation of semimartingales. We give its pathwise representation, It\^o-type isometry for martingales, and applications to harmonic analysis.

Probability · Mathematics 2024-12-25 Krzysztof Bogdan , Dominik Kutek , Katarzyna Pietruska-Pałuba

This article characterizes conjugates and subdifferentials of convex integral functionals over linear spaces of cadlag stochastic processes. The approach is based on new measurability results on the Skorokhod space and new interchange rules…

Optimization and Control · Mathematics 2018-12-12 Ari-Pekka Perkkiö , Erick Treviño-Aguilar

The first part of the present article consists in a survey about the dynamical constructive method designed using dynamical theories and dynamical algebraic structures. Dynamical methods uncovers a hidden computational content for numerous…

Algebraic Geometry · Mathematics 2023-09-06 Henri Lombardi , Assia Mahboubi

These lecture notes present an overview of equilibrium statistical mechanics of classical fluids, with special applications to the structural and thermodynamic properties of systems made of particles interacting via the hard-sphere…

Soft Condensed Matter · Physics 2014-06-24 Andrés Santos

A method of calculating a new class of symmetries is presented for partial differential equations. The method give a new dynamical solution for an isothermal and cylindrically symmetric hydrodynamics equations under self-gravity. The…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 Souichi Murata , Kazuhiro Nozaki

In this work we introduce a theory of stochastic integration with respect to general cylindrical semimartingales defined on a locally convex space $\Phi$. Our construction of the stochastic integral is based on the theory of tensor products…

Probability · Mathematics 2021-12-06 C. A. Fonseca-Mora

The authors present SHarmonic, a new implementation of the spherical harmonics targeted for electronic-structure calculations. Their approach is to use explicit formulas for the harmonics written in terms of normalized Cartesian…

Computational Physics · Physics 2025-10-08 Xavier Andrade , Jacopo Simoni , Yuan Ping , Tadashi Ogitsu , Alfredo A. Correa

This brief article reviews stochastic processes as relevant to dynamical models of wave-function collapse, and is supplemental material for the review article arXiv:1204.4325

Quantum Physics · Physics 2012-12-24 Angelo Bassi , Kinjalk Lochan , Seema Satin , Tejinder P. Singh , Hendrik Ulbricht

This paper is devoted to tangent martingales in Banach spaces. We provide the definition of tangency through local characteristics, basic $L^p$- and $\phi$-estimates, a precise construction of a decoupled tangent martingale, new estimates…

Probability · Mathematics 2020-09-22 Ivan S. Yaroslavtsev

The density hypothesis on random times becomes now a standard in modeling of risks. One of the basic reasons to introduce the density hypothesis is the desire to have a computable credit risk model. However, recent work shows that merely an…

Probability · Mathematics 2014-02-04 Shiqi Song

The aim of this work is to introduce a new stochastic volatility model for equity derivatives. To overcome some of the well-known problems of the Heston model, and more generally of the affine models, we define a new specification for the…

Pricing of Securities · Quantitative Finance 2014-09-19 José Da Fonseca , Claude Martini

Methods from the geometry of nonholonomic manifolds and Lagrange-Finsler spaces are applied in fractional calculus with Caputo derivatives and for elaborating models of fractional gravity and fractional Lagrange mechanics. The geometric…

Mathematical Physics · Physics 2011-06-03 Dumitru Baleanu , Sergiu I. Vacaru

This manuscript presents a novel framework that integrates higher-order symmetries and category theory into machine learning. We introduce new mathematical constructs, including hyper-symmetry categories and functorial representations, to…

Machine Learning · Computer Science 2024-09-19 Ronald Katende