Fast Sequential Monte Carlo Methods for Counting and Optimization - Info and Reading Options
By Reuven Y. Rubinstein, Ad Ridder and Radislav Vaisman
"Fast Sequential Monte Carlo Methods for Counting and Optimization" was published by Wiley & Sons, Incorporated, John in 2013 - New Jersey - Hoboken, New Jersey, the book is classified in bibliography genre, it has 208 pages and the language of the book is English.
“Fast Sequential Monte Carlo Methods for Counting and Optimization” Metadata:
- Title: ➤ Fast Sequential Monte Carlo Methods for Counting and Optimization
- Authors: Reuven Y. RubinsteinAd RidderRadislav Vaisman
- Language: English
- Number of Pages: 208
- Publisher: ➤ Wiley & Sons, Incorporated, John
- Publish Date: 2013
- Publish Location: ➤ New Jersey - Hoboken, New Jersey
- Genres: bibliography - Electronic books.
- Dewey Decimal Classification: 518/.282
- Library of Congress Classification: T57.64
“Fast Sequential Monte Carlo Methods for Counting and Optimization” Subjects and Themes:
- Subjects: Mathematical optimization - Monte carlo method - Monte Carlo method - MATHEMATICS - Numerical Analysis
Edition Specifications:
- Number of Pages: 1 online resource.
Edition Identifiers:
- The Open Library ID: OL33480826M - OL21511006W
- Library of Congress Control Number (LCCN): ^^2013019187
- ISBN-13: 9781118612378 - 9781118612316 - 9781118612354 - 9781118612323 - 9781306118422
- All ISBNs: ➤ 9781118612378 - 9781118612354 - 1118612353 - 9781118612316 - 1118612310 - 111861237X - 9781118612323 - 1118612329 - 9781306118422 - 1306118425 - 9781118612262 - 1118612264
AI-generated Review of “Fast Sequential Monte Carlo Methods for Counting and Optimization”:
"Fast Sequential Monte Carlo Methods for Counting and Optimization" Description:
Harvard Library:
This book presents the first comprehensive account of fast sequential Monte Carlo (SMC) methods for counting and optimization at an exceptionally accessible level. Written by authorities in the field, it places great emphasis on cross-entropy, minimum cross-entropy, splitting, and stochastic enumeration. The overall aim is to make SMC methods accessible to readers who want to apply and to accentuate the unifying and novel mathematical ideas behind SMC in their future studies or work.
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