Monte Carlo Markov chains (MCMCs) method
A hamiltonian Monte Carlo method for non-smooth energy sampling
... using Markov chain Monte Carlo (MCMC) sampling techniques ...Hamiltonian Monte Carlo (HMC) sampling technique has recently been proposed in [8], [13], ...simulated chains are ...
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Forward Event-Chain Monte Carlo: Fast sampling by randomness control in irreversible Markov chains
... Event-Chain Monte Carlo. This method allows for a fast and global exploration of the sampling space, thanks to a new lifting implementation which leads to a minimal randomization and an alleviation ...
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A History of Markov Chain Monte Carlo--Subjective Recollections from Incomplete Data--
... that Markov chains could be used in a wide variety of situations only came (to mainstream statisticians) with Gelfand and Smith (1990), de- spite earlier publications in the statistical literature like ...
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Parallelized Stochastic Gradient Markov Chain Monte Carlo Algorithms for Non-Negative Matrix Factorization
... celeration method, called the Richardson-Romberg extrapolation, which simply boils down to running two SGLD chains in parallel with different step ...two chains are started from the same initial ...
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A hamiltonian Monte Carlo method for non-smooth energy sampling
... using Markov chain Monte Carlo (MCMC) sampling techniques ...Hamiltonian Monte Carlo (HMC) sampling technique has recently been proposed in [8], [13], ...simulated chains are ...
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Efficient Bayesian Computation by Proximal Markov Chain Monte Carlo: When Langevin Meets Moreau.
... (a) (b) (c) Figure 1: (a) Original Boat image (256 × 256 pixels), (b) Blurred image, (c) MAP estimate computed with [Afonso et al., 2011]. Moreover, Section 4 shows the magnitude of the marginal 90% credibility regions ...
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What causes the forecasting failure of Markov-switching models ? A Monte Carlo study
... to the estimation procedure 6 . We apply this decomposition in the Monte Carlo design described above. For each DGP analyzed in Section 3, the relative weights of each component in absolute value for the ...
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Estimating the granularity coefficient of a Potts-Markov random field within an Markov Chain Monte Carlo algorithm
... proposed method performs as well as if β was perfectly ...(proposed method) as well as the standard deviations of the estimates (results are displayed as [mean ± standard ...proposed method and ...
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Monte Carlo Beam Search
... Nested Monte-Carlo Search parallelizes quite well until at least 64 cores ...of Monte-Carlo Beam Search is even more simple than the paralleliza- tion of Nested Monte-Carlo ...
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Hidden hybrid Markov/semi-Markov chains.
... hybrid Markov/semi-Markov chains, ...semi-Markov chains as de- fined in Guédon (2003) can be seen as hidden hybrid Markov/semi-Markov chains since the absorbing ...
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A regression Monte-Carlo method for Backward Doubly Stochastic Differential Equations
... (Paris, 1995–1996), 177–191, Pitman Res. Notes Math. Ser., 364, Longman, Harlow, 1997. [5] Bouchard B., Touzi N., Discrete time approximation and Monte Carlo simulation of backward sto- chastic differential ...
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Optimized Population Monte Carlo
... the fact that log π might not be necessarily log-concave at e µ (t) n , so that ∇ 2 log π( µ e (t) n ) might be non invertible. We take here advantage of the trajectory tracking inherent to the AIS method, by ...
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A New Walk on Equations Monte Carlo Method for Linear Algebraic Problems
... continuation method used in the functional analysis ...uses Monte Carlo estimates of the forward and adjoint ...a Monte Carlo algorithm for matrix inversion is proposed and ...
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An Overview of Cloud Simulation Enhancement using the Monte-Carlo Method
... V. C ONCLUSION In this paper, we propose a Monte-Carlo simulation ex- tension to a discrete event simulator based on SimGrid. This extension provides stochastic predictions which are more informative than ...
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Towards the parallelization of Reversible Jump Markov Chain Monte Carlo algorithms for vision problems
... L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignemen[r] ...
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Metamodel-based Markov-Chain-Monte-Carlo parameter inversion applied in eddy current flaw characterization
... numerical solvers could be used, e.g., Finite Element Method (FEM), yet their efficiency relies on the number of measurement points that one needs to simulate. The analysis performed in this section in commonly ...
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Nested Monte-Carlo Search
... Morpion Solitaire is an NP-hard puzzle and the high score is inapproximable within n 1− for any > 0 unless P = NP [Demaine et al., 2006]. A move consists in adding a circle such that a line containing five circles ...
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Reflexive Monte-Carlo Search
... The code for the meta-meta level is similar to the code for the meta-level. In fact all the meta-levels above the ground level use a very similar code. There is no theoretical limitation to the number of levels of ...
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Troc Combinatoire à Monte-Carlo
... de Monte-Carlo 1 Allocation Distribuée de Ressources Indivisibles Cet article s’intéresse au problème de partage de ressources indivisibles par des mécanismes distri- ...
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Méthodes de Monte-Carlo en finance
... où r s désigne le taux d’intérêt instantané, τ t,T l’ensemble des temps d’arrêt à valeurs dans [t, T ], Φ la fonction payoff et (F t ) une filtration donnée. cette for- mule telle qu’elle est explicitée est presque ...
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