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Lecture

Partial Derivatives

In course

MATH-431: Theory of stochastic calculus

Introduction to the mathematical theory of stochastic calculus: construction of the Ito stochastic integral, proof of the Ito formula, introduction to stochastic differential equations, Girsanov's theorem and the Feynman-Kac formula, the martingale represe ...

Description

This lecture covers the concept of partial derivatives, focusing on the computation and interpretation of these derivatives in various scenarios. It also discusses the properties of saddle points, local maxima, and minima in multivariable functions.

Instructors (2)

Thomas Mountford

D'origine britannique, né en 1961. Il a reçu la bourse présidentielle des jeunes investisseurs (Presidential Young Investigator Grant) en 1990 et le prix de la Fraternité Sloan (Sloan Fellowship) en 1991. Son travail montre que les valeurs critiques d'une classe large de de systèmes de particules proches sont égales à 1, et que, suite à plusieurs travaux sur la trajectoire du mouvement brownien, incluant une simulation numérique, le nombre d'îlots browniens en 2 dimensions tend vers l'infini quand leurs tailles tendent vers 0. Il reçoit le prix Rosenbaum en 1993 lui ouvrant ainsi les portes du Isaac Newton Institute à Cambridge. Il est également décoré par le prix Rollo Davidson en 1995 et nommé membre honoraire de l'Institute of Mathematical Statistics en 2001. Assistant Profeseur de Mathematique a UCLA 1987- 1991 Associate Professeur de Mathematique a UCLA 1991-1993 Professeur de Mathematique a UCLA 1993-2001 Professeur Departement de mathématiques, EPFL dès 2001

Robert Dalang

Robert Dalang, né en 1961, a reçu le diplôme de Mathématicien-EPFL en 1983 et est lauréat du Prix Dommer. Il passe l'année 1985-86 à Cornell University (USA) comme chercheur invité. Il obtient le doctorat au Département de mathématiques de l'EPFL en 1987. Son domaine de spécialisation est la théorie des processeurs stochastiques. En 1987, Robert Dalang est nommé professeur assistant au Département de statistiques de l'Université de Californie à Berkeley (USA). En 1988, il reçoit une bourse post-doctorale du Fonds national scientifique américain et effectue des recherches sur les propriétés markoviennes de processus stochastiques à plusieurs paramètres. En 1990, il est nommé à Tufts University (Boston, USA). Il est promu professeur associé en mai 1993. Une partie importante de ses recherches se font dans le cadre de contrats avec le Fonds national scientifique américain et l'Office de la recherche de l'armée américaine. En collaboration avec le Prof. R. Cairoli du Département de mathématiques de l'EPFL, il a écrit un livre sur l'optimisation stochastique séquentielle publié en 1996 aux éditions John Wiley. M. Dalang est nommé professeur extraordinaire de probabilités au Département de mathématiques en 1995. Il y poursuit des travaux de recherche en processus stochastiques et probabilité appliquée et participe à l'enseignement des processus stochastiques, de la théorie des probabilités et des cours de mathématiques aux sections d'ingénieurs. Il dirige régulièrement des thèses de doctorats, est éditeur de plusieurs journaux de recherche mathématique et travail en collaboration avec des chercheurs de plusieurs universités européennes et américaines.

Official source

Ontological neighbourhood

Mathematics

Analysis: Calculus

Related concepts (25)

Partial derivative

In mathematics, a partial derivative of a function of several variables is its derivative with respect to one of those variables, with the others held constant (as opposed to the total derivative, in which all variables are allowed to vary). Partial derivatives are used in vector calculus and differential geometry. The partial derivative of a function with respect to the variable is variously denoted by It can be thought of as the rate of change of the function in the -direction.

Maximum and minimum

In mathematical analysis, the maximum and minimum of a function are, respectively, the largest and smallest value taken by the function. Known generically as extremum, they may be defined either within a given range (the local or relative extrema) or on the entire domain (the global or absolute extrema) of a function. Pierre de Fermat was one of the first mathematicians to propose a general technique, adequality, for finding the maxima and minima of functions.

Derivative

In mathematics, the derivative shows the sensitivity of change of a function's output with respect to the input. Derivatives are a fundamental tool of calculus. For example, the derivative of the position of a moving object with respect to time is the object's velocity: this measures how quickly the position of the object changes when time advances. The derivative of a function of a single variable at a chosen input value, when it exists, is the slope of the tangent line to the graph of the function at that point.

Differentiable function

In mathematics, a differentiable function of one real variable is a function whose derivative exists at each point in its domain. In other words, the graph of a differentiable function has a non-vertical tangent line at each interior point in its domain. A differentiable function is smooth (the function is locally well approximated as a linear function at each interior point) and does not contain any break, angle, or cusp. If x0 is an interior point in the domain of a function f, then f is said to be differentiable at x0 if the derivative exists.

Total derivative

In mathematics, the total derivative of a function f at a point is the best linear approximation near this point of the function with respect to its arguments. Unlike partial derivatives, the total derivative approximates the function with respect to all of its arguments, not just a single one. In many situations, this is the same as considering all partial derivatives simultaneously. The term "total derivative" is primarily used when f is a function of several variables, because when f is a function of a single variable, the total derivative is the same as the ordinary derivative of the function.

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