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Gibbs sampling / Particle filter / Markov chain Monte Carlo / Importance sampling / Random variable / Variance / Bayesian network / Resampling / Rejection sampling / Statistics / Monte Carlo methods / Probability and statistics


Exact and Approximate Sampling by Systematic Stochastic Search
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Document Date: 2009-03-21 12:47:00

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File Size: 1,02 MB

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City

Cambridge / Clearwater Beach / /

Company

NTT Communication Science Laboratories / Neural Information Processing Systems / Wilson / MIT Press / Eli Lilly Corporation / Monte Carlo / Google / /

Country

Jordan / United States / /

IndustryTerm

recursive algorithm / poor quality approximate solution / systematic search / approximate algorithms / search tree expansion / deterministic systematic search / local search / nonadaptive algorithm / causal networks / machinery / medical diagnosis network / systematic search algorithms / sigmoid belief networks / candidate solution / deterministic search / typical network / partial solutions / variational inference algorithms / particle filtering algorithms / deterministic fixed-point algorithms / search behavior / /

Organization

Royal Statistical Society / National Science Foundation / MIT / US Federal Reserve / /

Person

Kevin Murphy / Eric Jonas / Joshua Tenenbaum / Jonathan Gonda / Keith Bonawitz / Nando de Freitas / Daniel Roy / /

Position

D. J. / adaptive inference planner / /

ProvinceOrState

Florida / Massachusetts / /

PublishedMedium

Journal of the Royal Statistical Society / Physical Review / Journal of Artificial Intelligence Research / /

Technology

sampling algorithms / variational inference algorithms / artificial intelligence / particle filtering algorithms / Adaptive Sequential Rejection Algorithm / simulation / deterministic fixed-point algorithms / recursive algorithm / nonadaptive algorithm / systematic search algorithms / /

URL

http /

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