Monte-Carlo Markov Chains
Forward Event-Chain Monte Carlo: Fast sampling by randomness control in irreversible Markov chains
... ( 2018 ). Ideally, one would like to find the optimal set of directions necessary for ergodicity and allowing for an efficient exploration and update the direction among this set at events. But, contrary to physics, many ...
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Identification of random variables via Markov Chain Monte Carlo: benefits on reliability analysis
... 2 NUMERICAL SIMULATION The purpose of the numerical simulation is the evaluation of the algorithm convergence as a func- tion of the number N of available observations and of the length M of the generated chains ...
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High dimensional Markov chain Monte Carlo methods : theory, methods and applications
... Finally, we present some numerical simulations to support our findings, and besides some algorithmic strategies to handle the transient phase of the algorithm. Indeed, our optimal scaling result can be applied only to ...
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Parallelized Stochastic Gradient Markov Chain Monte Carlo Algorithms for Non-Negative Matrix Factorization
... SGLD chains in SGRRLD ...two chains in SGRRLD can al- ready be run in parallel whereas in P-SGRRLD we further increase this parallelism and run the update equations of each chain in paral- lel, as in ...
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Population Monte Carlo
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omputation. JASA 96, 561{573. Ma
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hern, S.N. and Peruggia, M. (2000) Importan
e link fun
tion estimation for Markov Chain Monte Carlo methods. J. Comput. Graph. Statist. 9, 99{121. Mengersen, K.L. ...
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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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Pépite | Méthodes quasi-Monte Carlo et Monte Carlo : application aux calculs des estimateurs Lasso et Lasso bayésien
... [12] N. Metropolis, A.W. Rosenbluth, M.N. Rosenbluth, A.H. Teller and E. Teller, Equations of state calculations by fast computing machines, journal of Chemical Physics, vol. 21 no. 6 1087–1092 (1953). [13] S.P. Meyn, ...
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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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Subgeometric ergodicity of Markov chains
... is a nonnegative function which can be computed explicitly. As emphasized in [RR04, section 3.5], quantitative bounds have a sub- stantial history in Markov chain theory. Applications are numerous including ...
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On Markov chain Monte Carlo methods for tall data
... The possibility to use an unbiased estimator of γ comes at a price: first, the asymptotic vari- ance σ lim 2 in (4) of an MCMC estimator based on a pseudo-marginal chain will always be larger than that of an estimator ...
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Stochastic Gradient Richardson-Romberg Markov Chain Monte Carlo
... Our results show that by only using a first-order numerical integrator, the proposed approach can achieve the theoretical accuracy of methods that are based on higher-order integrators, such as the ones given in [10]. ...
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Nested Monte-Carlo Search
... Figure 8: Distributions of the scores for Morpion Solitaire Figure 9: Distributions of the scores for Morpion Solitaire with memorization of the best sequence In Morpion Solitaire a nested search of level l is 200 times ...
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Reflexive Monte-Carlo Search
... 4 Experimental Results For the experiments, the programs run on a Pentium 4 cadenced at 2.8 GHz with 1 GB of RAM. All experiments concern the non-touching version. Table 1 gives the lengths of the best games obtained ...
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Méthodes de Monte Carlo en Vision Stéréoscopique
... Il nous paraˆıt cependant moins intuitif de mod´ eliser la matrice de covariance in- verse, plutˆ ot que la matrice de covariance elle-mˆ eme. De plus, bien souvent, pour des raisons de limitation du temps de calcul, des ...
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Contributions to Monte Carlo Search
... 6.7 Conclusion This work can be extended in several ways. For the time being, we used the mean performance over a set of training problems to discriminate between different candidate algorithms. One direction for future ...
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Addressing nonlinearities in Monte Carlo
... Richard Fournier 3 , Mathieu Galtier 7 , Jacques Gautrais 8 , Anaïs Khuong 8 , Lionel Pelissier 9 , Benjamin Piaud 5 , Maxime Roger 7 , Guillaume Terrée 2 & Sebastian Weitz 1,2 Monte Carlo is famous for ...
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Parallel Nested Monte-Carlo search
... reflexive Monte-Carlo algorithm was shown to be effective for Morpion Solitaire ...Reflexive Monte-Carlo search is close in spirit to nested rollouts except that the base level plays random ...
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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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Monte Carlo Beam Search
... Monte-Carlo Beam Search Tristan Cazenave Abstract—Monte-Carlo Tree Search is state of the art for multiple games and for solving puzzles such as Morpion ...Nested Monte-Carlo ...
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Calcul d’Intégral par la Méthode de Monte-Carlo
... de Monte-Carlo Les méthodes de Monte-Carlo sont particulièrement utilisées pour calculer des intégrales en dimensions plus grandes que 1 (en particulier, pour calculer des surfaces, des ...
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