On the Concentration Properties of Interacting Particle Processes

1. Auflage 2012
ISBN: 978-1-60198-512-5
Verlag: Now Publishers

Buch, Englisch, Band 10, 176 Seiten, Format (B × H): 156 mm x 234 mm

Reihe: Foundations and Trends® in Machine Learning

This book presents some new concentration inequalities for Feynman-Kac particle processes. It analyzes different types of stochastic particle models, including particle profile occupation measures, genealogical tree based evolution models, particle free energies, as well as backward Markov chain particle models. It illustrates these results with a series of topics related to computational physics and biology, stochastic optimization, signal processing and Bayesian statistics, and many other probabilistic machine learning algorithms. Special emphasis is given to the stochastic modeling, and to the quantitative performance analysis of a series of advanced Monte Carlo methods; including particle filters, genetic type island models, Markov bridge models, and interacting particle Markov chain Monte Carlo methodologies.

Autoren/Hrsg.

Del Moral, Pierre

Hu, Peng

Wu, Liming

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

1: Stochastic particle methods 2: Some application domains 3: Feynman-Kac semigroup analysis 4: Empirical processes 5: Interacting empirical processes 6: Feynman-Kac particle processes. References