[PDF] Top 20 A random imputation principle : the stochastic EM algorithm
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A random imputation principle : the stochastic EM algorithm
... 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] ... Voir le document complet
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EVALUATION OF A STOCHASTIC REVERBERATION MODEL BASED ON THE IMAGE SOURCE PRINCIPLE
... evaluate the performance of the EM algorithm, we used synthetic RIRs generated by Roomsimove ...is a MATLAB toolbox that simulates a parallelepipedic room, and allows us to ... Voir le document complet
8
Estimating the granularity coefficient of a Potts-Markov random field within an MCMC algorithm
... approximate the normalizing constant ...on a combination of both. A survey of the state-of-the-art approximation methods up to 2004 has been presented in ...[20]. The methods ... Voir le document complet
15
The stochastic Auxiliary Problem Principle in Banach spaces: measurability and convergence
... Abstract The stochastic Auxiliary Problem Principle (APP) algorithm is a general Stochastic Approximation (SA) scheme that turns the resolution of an original optimization ... Voir le document complet
35
A Smoothing Stochastic Phase Retrieval Algorithm for Solving Random Quadratic Systems
... recovering a signal from the squared modulus of some linear transforms, which has proved efficient in in various applications such as, optics [1], astronomy [2] and X-ray crystallography [3, 4, 5, ...solve ... Voir le document complet
6
A Stochastic Dynamic Principle for Hybrid Systems with Execution Delay and Decision Lags
... explains the motivation of including the exe- cution delay and the decision lag constraints in the model, as well as the method used to incorporate these constraints in the ... Voir le document complet
7
The algorithm for the analysis of combined chaotic-stochastic processes
... from stochastic signal analysis (nonstationary Gaussian processes, statistics from limit theo- rems by Nordin, Hurst exponent), and nonlinear (chaotic) dynamical system analysis (phase portrait, phase delayed ... Voir le document complet
9
Asymptotic description of stochastic neural networks. I. Existence of a large deviation principle
... study the asymptotic behaviour and large deviations of a net- work of interacting neurons when the number of neurons becomes ...of the continuous time dynamics of networks of rate neurons, ... Voir le document complet
10
A new stochastic optimization algorithm to decompose large nonnegative tensors
... information, the volume of available data is continually ...In the field of “Big Data”, the ability to efficiently process and analyse large data sets has become a key ...tensors. A ... Voir le document complet
13
Stochastic modeling of random heterogeneous materials
... that the microstructure C and the mesostructure ˜C have the same homogenized ...words, the mesoscopic tensor random fields thus defined satisfy the macroscopic consistency ... Voir le document complet
163
A minimax and asymptotically optimal algorithm for stochastic bandits
... Notably, the OC-UCB algorithm satisfies another worthwhile property of finite-time instance near-optimality , see Section 2 of Lattimore ( 2015 ) for a detailed ...forward the kl-UCB ++ ... Voir le document complet
16
Quenched invariance principle for random walks on Delaunay triangulations
... [FGG12], the existence of an harmonic corrector was recently established by a different (constructive) ...Nevertheless, the authors of this paper obtained the sublinearity of the ... Voir le document complet
34
A fast algorithm for the two dimensional HJB equation of stochastic control
... Unité de recherche INRIA Rocquencourt Domaine de Voluceau - Rocquencourt - BP 105 - 78153 Le Chesnay Cedex France Unité de recherche INRIA Lorraine : LORIA, Technopôle de Nancy-Brabois -[r] ... Voir le document complet
25
A biased random key genetic algorithm applied to the electric distribution network reconfiguration problem
... presents a biased random-key genetic algorithm (BRKGA) to solve the electric distribution network reconfiguration problem ...(DNR). The DNR is one of the most studied ... Voir le document complet
18
A stochastic approximation type EM algorithm for the mixture problem
... 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] ... Voir le document complet
34
Annealed invariance principle for random walks on random graphs generated by point processes in $\mathbb{R}^d$
... 4: the diffusion coefficient is nondegenerate From now on, we assume that the hypotheses of Proposition 4 are satisfied and we prove it implies the non-degeneracy of the limiting Brownian ... Voir le document complet
32
On the estimation of the latent discriminative subspace in the Fisher-EM algorithm
... Abstract: The Fisher-EM algorithm has been recently proposed in [2] for the simultaneous visualization and clustering of high-dimensional ...on a discriminative latent mixture model ... Voir le document complet
19
A fast EM algorithm for Gaussian model-based source separation
... proposed a new EM algorithm for the FASST source sep- aration framework, which greatly reduces its computational cost while retaining its ability of exploiting advanced source ...addition, ... Voir le document complet
6
Analysis of a stack algorithm for random length packet communication
... 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] ... Voir le document complet
24
A perfect sampling algorithm of random walks with forbidden arcs
... from the fact that the random walk (discrete or continuous) with forbidden arcs is not monotone so that classical perfect sampling techniques based on the simulation of extreme points ( [Propp ... Voir le document complet
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