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Fast Sequential Monte Carlo Methods for Counting and Optimization by Radislav Vaisman, Ad Ridder, Reuven Y. Rubinstein

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Index

n-step-look-ahead

adaptive splitting

associated stochastic problem

asymptotic optimality

basic Monte Carlo

biadjacency matrix

binary contingency tables

Boltzmann distribution

bounded relative error

capture-recapture

complexity theory

confidence interval

crude Monte Carlo

decreasing sets

degeneracy

direct estimation

elite set

entropy

cross-

differential

joint

Kullback-Leibler

relative

Shannon

exponential change of measure

exponential-time estimator

fixed level splitting

fully polynomial-time randomized approximation scheme

Gibbs sampler

graph coloring

Hamilton cycles

importance sampling

independent sets

Jensen's inequality

knapsack problem

Kullback-Leibler divergence

likelihood ratio

logarithmic efficiency

Markov decision process

mastermind game

max-cut problem

maximum likelihood

maximum satisfiability problem

minimum cross-entropy

basic

classic

general

indicator

Jaynes

parametric

single

multi-level approach

multiple-event probability

multiple-OSLA

nominal parameter

one-step-look-ahead

optimization

combinatorial

continuous

noisy

oracle

parameterized family

parametric cross-entropy\hb minimization

perfect matching

permanent

permutation Monte Carlo

Pincus theorem

polynomial-time estimator

prior pdf

rare-event probability

rarity parameter

reference parameter

reinforcment learning

relative error

reliability model

RSA problem

sample performance function

satisfiability problem

screening

self-avoiding walk

set covering problem

smoothed updating

splitting method

splitting parameter ...

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