Skip to Content
Fast Sequential Monte Carlo Methods for Counting and Optimization
book

Fast Sequential Monte Carlo Methods for Counting and Optimization

by Reuven Y. Rubinstein, Ad Ridder, Radislav Vaisman
December 2013
Intermediate to advanced
208 pages
5h 40m
English
Wiley
Content preview from Fast Sequential Monte Carlo Methods for Counting and Optimization

Chapter 3

Minimum Cross-Entropy Method

This chapter deals with the minimum cross-entropy method, also known as the MinxEnt method for combinatorial optimization problems and rare-event probability estimation. The main idea of MinxEnt is to associate with each original optimization problem an auxiliary single-constrained convex optimization program in terms of probability density functions. The beauty is that this auxiliary program has a closed-form solution, which becomes the optimal zero variance solution, provided the “temperature” parameter is set to minus infinity. In addition, the associated pdf based on the product of marginals obtained from the joint optimal zero variance pdf coincide with the parametric pdf of the cross-entropy (CE) method. Thus, we obtain a strong connection between CE and MinxEnt, providing solid mathematical foundations.

3.1 Introduction

Let c03-math-0001 be a continuous function defined on some closed bounded c03-math-0002-dimensional domain c03-math-0003. Assume that c03-math-0004 is a unique minimum point over . The following theorem is due to Pincus [94].

Theorem 3.1
Let be a real-valued continuous function ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.

Read now

Unlock full access

More than 5,000 organizations count on O’Reilly

AirBnbBlueOriginElectronic ArtsHomeDepotNasdaqRakutenTata Consultancy Services

QuotationMarkO’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.
Julian F.
Head of Cybersecurity
QuotationMarkI wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.
Addison B.
Field Engineer
QuotationMarkI’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.
Amir M.
Data Platform Tech Lead
QuotationMarkI'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.
Mark W.
Embedded Software Engineer

You might also like

Derivatives Analytics with Python: Data Analysis, Models, Simulation, Calibration and Hedging

Derivatives Analytics with Python: Data Analysis, Models, Simulation, Calibration and Hedging

Yves Hilpisch

Publisher Resources

ISBN: 9781118612354Purchase book