Results 31 to 40 of about 3,977,371 (295)
A sampling algorithm for segregation analysis [PDF]
Genetics Selection Evolution, 2001 Methods for detecting Quantitative Trait Loci (QTL) without markers have generally used iterative peeling algorithms for determining genotype probabilities. These algorithms have considerable shortcomings in complex pedigrees. A Monte Carlo Markov chain (MCMC) method which samples the pedigree of the whole population jointly is described.
Henshall John, Tier Bruce
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Rejection Sampling-based Multi-start Algorithms for Global Optimization [PDF]
Jisuanji gongchengFinding the global minimum of complex functions has broad applications in engineering computations and artificial intelligence. The multi-start algorithm is a commonly used heuristic approach for this; however, it suffers from low computational ...
LI Rui, WEN Minhua, FAN Yin, XU Dongyang, ZHANG Zhanbing, LIN Xinhua
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Rare event sampling with stochastic growth algorithms
EPJ Web of Conferences, 2013 We discuss uniform sampling algorithms that are based on stochastic growth methods, using sampling of extreme configurations of polymers in simple lattice models as a motivation.
Prellberg Thomas
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Sampling and reconstructing signals from a union of linear subspaces
, 2011 In this note we study the problem of sampling and reconstructing signals which are assumed to lie on or close to one ofseveral subspaces of a Hilbert space.
Blumensath, Thomas, Thomas Blumensath
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Fast algorithms for band-limited extrapolation by over sampling and Fourier series
EURASIP Journal on Advances in Signal Processing, 2023 In this paper, fast algorithms for the extrapolation of band-limited signals are presented by the sampling theorem and Fourier series in the case of over sampling. Assume the band-limited signal is known in a finite interval. We update the signal outside
Weidong Chen
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On Thompson Sampling with Langevin Algorithms
CoRR, 2020 Thompson sampling for multi-armed bandit problems is known to enjoy favorable performance in both theory and practice. However, it suffers from a significant limitation computationally, arising from the need for samples from posterior distributions at every iteration.
Mazumdar, Eric +4 more
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On the use of biased-randomized algorithms for solving non-smooth optimization problems
, 2020 Soft constraints are quite common in real-life applications. For example, in freight transportation, the fleet size can be enlarged by outsourcing part of the distribution service and some deliveries to customers can be postponed as well; in inventory ...
Juan A.A. +4 more
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Sampling using a ‘bank’ of clues [PDF]
, 2010 An easy-to-implement form of the Metropolis Algorithm is described which, unlike most standard techniques, is well suited to sampling from multi-modal distributions on spaces with moderate numbers of dimensions (order ten) in environments typical of ...
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Investigation on the sampling size optimisation in gear tooth surface measurement using a Co-ordinate Measuring Machine [PDF]
, 2004 Co-ordinate Measuring Machines (CMMs) are widely used in gear manufacturing industry. One of the main issues for contact inspection using a CMM is the sampling technique.
Cheng, K, Webb, D, Gao, CH
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Optimal Character Distance Sampling for Exact String Matching Through Set Cover Reformulation
IEEE AccessCharacter Distance Sampling (CDS) is part of a broader class of string matching techniques that leverage sampling strategies. These methods provide an effective compromise between the prohibitive space requirements of offline approaches and the high ...
Simone Faro +2 more
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