Sampling algorithms
Calculating partial expected value of perfect information via Monte Carlo sampling algorithms
... Monte-Carlo sampling algorithm followed by some variants which are valuable in certain ...of sampling error on these estimates is covered including a bias caused by maximisation within nested ...
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Fast MCMC Sampling Algorithms on Polytopes
... 1970). Sampling algorithms are a prerequisite for applying Monte Carlo methods to order to approximate expectations and other ...(MCMC) algorithms; for in- stance, see the handbook by Brooks et ...
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Transdimensional sampling algorithms for Bayesian variable selection in classification problems with many more variables than observations
... We suggest using the general model proposal with all algorithms except the H-H algorithm, as it will lead to better exploration of the model space and an increase in the ESS. The increase is more pronounced when n ...
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Visual inspection : image sampling, algorithms and architectures
... This technique assumes the sensor’s active area to be pixel shaped, and its response to be an unbiased average o f the light intensity distributed across its surface. However, for practical sensors, even if the sensor ...
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Vectorized Discrete Gaussian Sampling with SIMD Support
... Gaussian sampling, denoted by Sampleℤ, which is to sample from a discrete Gaussian distribution 𝐷 ℤ,𝜎,𝑐 over the integers ℤ with parameter σ > 0 and center c ∈ ℝ, is usually one of the subroutines in discrete ...
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Development and Validation of Optimization Methods for the Design of Protein Sequences and Combinatorial Libraries
... optimization algorithms for MSD must choose sequences to test much more carefully than would be required in single-state design (SSD) problems of equivalent combinatorial ...
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Differentiable Sampling with Flexible Reference Word Order for Neural Machine Translation
... gorithms require an expert policy, which produces the best next token given any model predicted pre- fix, and assume that policy can be efficiently com- puted from the reference. However, for struc- tured prediction ...
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Use of Domain Knowledge In University
... and sampling algorithms have been implemented and their performance is evaluated ...of sampling algorithm the dataset is first partitioned into a number of given partitions and then algorithm is ...
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Towards automatic model comparison : an adaptive sequential Monte Carlo approach
... of sampling algorithms, which combine importance sampling and ...SMC algorithms by em- ploying a variety of “adaptive” strategies, their use for Bayesian model comparison has not yet received ...
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Efficient simulation of gamma and variance gamma processes
... define algorithms that sample discrete-time paths of the gamma process and the variance gamma process, recursively halfing the sampling horizon, conditional on pre- viously generated values of the ...exact ...
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Log-concave sampling: Metropolis-Hastings algorithms are fast
... Metropolis algorithms: the proposal function p satisfies p(x, y) = p(y, ...these algorithms depends on the properties of the target density π, and the degree to which the proposal function p is suited for ...
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Rare event sampling with stochastic growth algorithms
... uniform sampling algorithms that are based on stochastic growth methods, using sampling of extreme configurations of polymers in simple lattice mod- els as a ...uniform sampling of equilibrium ...
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Monte Carlo methods
... are sampling algorithms that allow to com- pute these integrals numerically when they are not analytically ...Carlo algorithms, among which rejec- tion sampling, importance sampling and ...
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A Significant Unification of Checksums and Hash Tables Using AIT
... 200MB of ROM from our mobile telephones. This configuration step was time-consuming but worth it in the end. Along these same lines, we tripled the USB key speed of our system. We struggled to amass the necessary 10MB ...
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Quadratic Time, Linear Space Algorithms for Gram-Schmidt Orthogonalization and Gaussian Sampling in Structured Lattices
... lattice algorithms, it is very important to not only consider the number of arithmetic operations, but also the arithmetic precision required for the algorithms to be ...of algorithms that are not ...
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Freeze-dried plasma proteins are stable at room temperature for at least 1 year
... independent sampling by liquid chromatography and tandem mass spectrometry (LC–ESI–MS/MS), as correlated by the MASCOT, OMSSA, X!TANDEM and SEQUEST algorithms, showed that tryptic peptides from complement ...
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A comparative Study of Classification Algorithm for Printed Telugu Character Recognition
... The importance of the preprocessing stage of a character recognition system lies in its ability to remedy some of the problems that may occur due to some of the factors presented in above section. Thus, the use of ...
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Dueling Bandits with Qualitative Feedback
... DB algorithms for solving the QDB problem, this re- duction significantly worsens the performance—actually, in the QDB problem, the probability that one arm wins the duel over another arm can be directly estimated ...
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Multiple genotypes within aecial clusters in Puccinia graminis and Puccinia coronata: improved understanding of the biology of cereal rust fungi
... of sampling required and interpretations of viru- lence tests. Algorithms in population genetic analyses are often based on single isolates ...thus sampling in the aecial stage of cereal rust fungi ...
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Variational Particle Approximations
... Most approximate inference algorithms fall into two classes: Monte Carlo methods and variational methods. Monte Carlo methods generate samples from approximations to the posterior distribution that grow more ...
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