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A Monte-Carlo Method for Optimal Portfolios

A Monte-Carlo Method for Optimal Portfolios

... A Monte-Carlo Method for Optimal Portfolios * Jérôme Detemple † , René Garcia ‡ , Marcel Rindisbacher § Résumé / Abstract Cet article établit des résultats nouveaux sur ... Voir le document complet

50

A regression Monte-Carlo method for Backward Doubly Stochastic Differential Equations

A regression Monte-Carlo method for Backward Doubly Stochastic Differential Equations

... is a gap in the corresponding proofs because of similar measurability issues for (Y t ) and (Y t π ...in a more general ...corresponding Monte Carlo ...is a key ingredient of the ... Voir le document complet

39

A new Monte Carlo method for neutron noise calculations in the frequency domain

A new Monte Carlo method for neutron noise calculations in the frequency domain

... via Monte Carlo simu- lations. In 2013, a Monte Carlo algorithm was first proposed by Yamamoto in [ 8 ] in order to solve the transport equation in neutron noise ...is a ... Voir le document complet

11

A new deviational Asymptotic Preserving Monte Carlo method for the homogeneous Boltzmann equation

A new deviational Asymptotic Preserving Monte Carlo method for the homogeneous Boltzmann equation

... introduce a new Monte Carlo method for solving the Boltzmann model of rarefied gas ...The method works by reformulating the original problem through a micro-macro ... Voir le document complet

37

A boundary-based net-exchange Monte Carlo method for absorbing and scattering thick media

A boundary-based net-exchange Monte Carlo method for absorbing and scattering thick media

... the method, in particular its strict analogy with physical processes, and the ability to solve complex problems, while trying to improve convergence ...reverse Monte Carlo algorithms [6], that make ... Voir le document complet

25

A Time Monte Carlo method for addressing uncertainty in land-use change models

A Time Monte Carlo method for addressing uncertainty in land-use change models

... Time Monte Carlo method for addressing uncertainty in land-use change models Abstract: One of the main objectives of land use change models is to explore future land use ...including a ... Voir le document complet

23

A New Walk on Equations Monte Carlo Method for Linear Algebraic Problems

A New Walk on Equations Monte Carlo Method for Linear Algebraic Problems

... 25 A, 1113 Sofia, Bulgaria Abstract A new Walk on Equations (WE) Monte Carlo algorithm for Linear Algebra (LA) problem is proposed and ...on a non-discounted sum of an absorbed ... Voir le document complet

31

A Cumulative migration method for computing rigorous transport cross sections and diffusion coefficients for LWR lattices with Monte Carlo

A Cumulative migration method for computing rigorous transport cross sections and diffusion coefficients for LWR lattices with Monte Carlo

... codes for generating homogenized lattice few-group cross section data for deterministic full core simulation, such as MCNP [ 13 ], Serpent [ 14 ], ...firstly a continuous-energy Monte ... Voir le document complet

17

A hamiltonian Monte Carlo method for non-smooth energy sampling

A hamiltonian Monte Carlo method for non-smooth energy sampling

... proposed a solution to make feasible the use of Hamiltonian dynamics for sampling according to log-concave probability distributions with non-smooth energy ...Hamiltonian Monte Carlo meth- ... Voir le document complet

12

A new Monte Carlo method for getting the density of states of atomic cluster systems

A new Monte Carlo method for getting the density of states of atomic cluster systems

... novel Monte Carlo flat histogram algorithm is proposed to get the classical density of states in terms of the potential energy, g(E p ), for systems with continuous variables such as atomic ... Voir le document complet

16

A hamiltonian Monte Carlo method for non-smooth energy sampling

A hamiltonian Monte Carlo method for non-smooth energy sampling

... proposed a solution to make feasible the use of Hamiltonian dynamics for sampling according to log-concave probability distributions with non-smooth energy ...Hamiltonian Monte Carlo meth- ... Voir le document complet

11

A new Monte Carlo method for neutron noise calculations

A new Monte Carlo method for neutron noise calculations

... presented a new Monte Carlo method that solves neutron noise ...new method does not use any weight cancellation techniques, is faster than the method developed in [ 7 ] and is ... Voir le document complet

7

An Overview of Cloud Simulation Enhancement using the Monte-Carlo Method

An Overview of Cloud Simulation Enhancement using the Monte-Carlo Method

... notwithstanding a slight right skew and shift of the empirical makespan ...required for an execution is correct but the simulated distribution differs ...to a Normal distribution, and producing ... Voir le document complet

3

A Comparative Study of Monte-Carlo Methods for Multitarget Tracking

A Comparative Study of Monte-Carlo Methods for Multitarget Tracking

... several Monte-Carlo methods on the challenging case of tracking an un- known number of independent targets in a hostile environment of heavy level of false alarm (clutter) and very low probability of ... Voir le document complet

5

On variable splitting for Markov chain Monte Carlo

On variable splitting for Markov chain Monte Carlo

... of a hidden object of interest x ∈ R d based on (noisy) observations y ∈ R n ...stand for parameters of a given model in machine learning [1] or may represent a signal or image to be recovered ... Voir le document complet

4

On variable splitting for Markov chain Monte Carlo

On variable splitting for Markov chain Monte Carlo

... stand for parameters of a given model in machine learning [1] or may represent a signal or image to be recovered within an inverse ...[2]. A widely used optimization-based approach is the ... Voir le document complet

3

Monte-Carlo Hex

Monte-Carlo Hex

... test a completely different method that uses Monte-Carlo ...tried Monte-Carlo meth- ods with Hex, we did not use tree search and ...interest for Monte-Carlo ... Voir le document complet

9

Sequential Monte Carlo for rare event estimation

Sequential Monte Carlo for rare event estimation

... Introduction. Monte Carlo approach is a common tool to estimate the expectation of any function of a random object when analytical or numerical methods are not ...on a set which has ... Voir le document complet

32

Clock Monte Carlo methods

Clock Monte Carlo methods

... clock Monte Carlo technique for sampling each successive chain step in constant ...on a recently proposed factorized transition filter and its core features include its O(1) computational ... Voir le document complet

7

Variance Analysis for Monte Carlo Integration

Variance Analysis for Monte Carlo Integration

... [2009] for Poisson Disk sampling, for capacity constraint methods we choose the method of de Goes and colleagues ...stratum. For Poisson Disk sampling, there exist many algorithms in the ... Voir le document complet

15

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