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comparison doc/v2_planning/sampler.txt @ 1027:a1b6ccd5b6dc

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few comments added
author Yoshua Bengio <bengioy@iro.umontreal.ca>
date Fri, 03 Sep 2010 21:57:22 -0400
parents 790376d986a3
children 875d53754bd0
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1026:38f799f8b6cd 1027:a1b6ccd5b6dc
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2 Inference / Sampling committee: JB, GD, AC
3
1 OVERVIEW 4 OVERVIEW
2 ======== 5 ========
3 6
4 Before we start defining what a sampler is and how it should be defined in 7 Before we start defining what a sampler is and how it should be defined in
5 pylearn, we should first know what we're up against. 8 pylearn, we should first know what we're up against.
34 * Metropolis Hastings 37 * Metropolis Hastings
35 * Slice Sampling 38 * Slice Sampling
36 * Annealing 39 * Annealing
37 * Parallel Tempering, Tempered Transitions, Simulated Tempering 40 * Parallel Tempering, Tempered Transitions, Simulated Tempering
38 * Nested Sampling (?) 41 * Nested Sampling (?)
39 * Hamiltonian Monte Carlo 42 * Hamiltonian Monte Carlo --> or is it Hybrid Monte Carlo?
43
44 3. USAGE PATTERNS
45 =================
46
47 * MCMC methods have a usage pattern that is quite different from the kind of univariate sampling methods
48 needed for nice-and-easy parametric families.
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