Lectures on Stochastic Analysis
نویسنده
چکیده
2 Review of probability. 5 2.1 Properties of expectation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 Convergence of random variables. . . . . . . . . . . . . . . . . . . . . . . . . 5 2.3 Convergence in probability. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.4 Norms. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.5 Information and independence. . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.6 Conditional expectation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
منابع مشابه
NSF/CBMS Conference Analysis of Stochastic Partial Differential Equations
Ten Lectures on Analysis of Stochastic Partial Differential Equations, Davar Khoshnevisan (University of Utah) The following is a more detailed plan for the lectures.
متن کاملIntroductory Lectures on Stochastic Optimization
In this set of four lectures, we study the basic analytical tools and algorithms necessary for the solution of stochastic convex optimization problems, as well as for providing various optimality guarantees associated with the methods. As we proceed through the lectures, we will be more exact about the precise problem formulations, providing a number of examples, but roughly, by a stochastic op...
متن کاملA Tutorial Introduction to Stochastic Analysis and Its Applications
We present in these lectures, in an informal manner, the very basic ideas and results of stochastic calculus, including its chain rule, the fundamental theorems on the representation of martingales as stochastic integrals and on the equivalent change of probability measure, as well as elements of stochastic differential equations. These results suffice for a rigorous treatment of important appl...
متن کاملA Sparsity Preserving Stochastic Gradient Method for Composite Optimization
We propose new stochastic gradient algorithms for solving convex composite optimization problems. In each iteration, our algorithms utilize a stochastic oracle of the gradient of the smooth component in the objective function. Our algorithms are based on a stochastic version of the estimate sequence technique introduced by Nesterov (Introductory Lectures on Convex Optimization: A Basic Course, ...
متن کاملLectures on Stochastic Processes
3 4 CONTENTS 6 Markov chains: stationary distributions 35 6.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2007