Results 1  10
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236,753
On Stochastic Versions of the EM Algorithm
, 1995
"... We compare three different stochastic versions of the EM
algorithm: The SEM algorithm, the SAEM algorithm and the MCEM algorithm. We suggest that the most relevant contribution of the MCEM methodology is what we call the
simulated annealing MCEM algorithm, which turns out to be very close to SAEM. ..."
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Cited by 40 (1 self)
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We compare three different stochastic versions of the EM
algorithm: The SEM algorithm, the SAEM algorithm and the MCEM algorithm. We suggest that the most relevant contribution of the MCEM methodology is what we call the
simulated annealing MCEM algorithm, which turns out to be very close to SAEM
Stochastic Versions of the LaSalle Theorem
 J. Differential Equations
, 1999
"... The main aim of this paper is to establish stochastic versions of the wellknown LaSalle stability theorem. From these stochastic versions follow many classical results on stochastic stability. This shows clearly the power of our new results. ..."
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Cited by 17 (7 self)
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The main aim of this paper is to establish stochastic versions of the wellknown LaSalle stability theorem. From these stochastic versions follow many classical results on stochastic stability. This shows clearly the power of our new results.
Learning Stochastic Logic Programs
, 2000
"... Stochastic Logic Programs (SLPs) have been shown to be a generalisation of Hidden Markov Models (HMMs), stochastic contextfree grammars, and directed Bayes' nets. A stochastic logic program consists of a set of labelled clauses p:C where p is in the interval [0,1] and C is a firstorder r ..."
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Cited by 1193 (81 self)
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Stochastic Logic Programs (SLPs) have been shown to be a generalisation of Hidden Markov Models (HMMs), stochastic contextfree grammars, and directed Bayes' nets. A stochastic logic program consists of a set of labelled clauses p:C where p is in the interval [0,1] and C is a first
STOCHASTIC VERSIONS OF THE EM ALGORITHM by
"... Abstract: We comparetbree different stochastic versi?nsof the EMal~orithm: the SEM algorithm,.the Si\EM algorithm. ~dthe lvfCEMalgorithm. We suggest that the most relevant contribution ofthe MCElvf methodology is,!hat~e can.the simulated annealing MCEMalgorithm, whichtums<out lobe very Flose to. ..."
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Abstract: We comparetbree different stochastic versi?nsof the EMal~orithm: the SEM algorithm,.the Si\EM algorithm. ~dthe lvfCEMalgorithm. We suggest that the most relevant contribution ofthe MCElvf methodology is,!hat~e can.the simulated annealing MCEMalgorithm, whichtums<out lobe very Flose to
On the Selfsimilar Nature of Ethernet Traffic (Extended Version)
, 1994
"... We demonstrate that Ethernet LAN traffic is statistically selfsimilar, that none of the commonly used traffic models is able to capture this fractallike behavior, that such behavior has serious implications for the design, control, and analysis of highspeed, cellbased networks, and that aggrega ..."
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Cited by 2212 (46 self)
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discussion of the underlying mathematical and statistical properties of selfsimilarity and their relationship with actual network behavior. We also present traffic models based on selfsimilar stochastic processes that provide simple, accurate, and realistic descriptions of traffic scenarios expected during
The Cyclical Behavior of Equilibrium Unemployment and Vacancies
 American Economic Review
, 2005
"... This paper argues that a broad class of search models cannot generate the observed businesscyclefrequency fluctuations in unemployment and job vacancies in response to shocks of a plausible magnitude. In the U.S., the vacancyunemployment ratio is 20 times as volatile as average labor productivity ..."
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Cited by 869 (23 self)
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productivity, while under weak assumptions, search models predict that the vacancyunemployment ratio and labor productivity have nearly the same variance. I establish this claim both using analytical comparative statics in a very general deterministic search model and using simulations of a stochastic version
A stochastic version of general recognition theory
 Journal of Mathematical Psychology
, 2000
"... General recognition theory (GRT) is a multivariate generalization of signal detection theory. Past versions of GRT were static and lacked a process interpretation. This article presents a stochastic version of GRT that models momentbymoment fluctuations in the output of perceptual channels via a m ..."
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Cited by 45 (1 self)
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General recognition theory (GRT) is a multivariate generalization of signal detection theory. Past versions of GRT were static and lacked a process interpretation. This article presents a stochastic version of GRT that models momentbymoment fluctuations in the output of perceptual channels via a
On a stochastic version of the plenacoustic function
 IEEE International Conference on Acoustics, Speech, and Signal Processing
, 2006
"... In this paper, we model a spatially varying channel where a source is moving along a random trajectory with respect to a fixed receiver. The aim is to compute the power spectral density corresponding to the channel impulse response as a function of temporal and spatial frequencies. The trajectory of ..."
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Cited by 4 (3 self)
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of the source follows an autoregressive model where the poles of the system control the smoothness of the path. Theoretical results are presented for the AR2 case and generalized to any ARn systems. Simulations results are shown and compared to the presented theory. The stochastic plenacoustic function analyzed
A stochastic version of the Eigen model
, 901
"... We exhibit a stochastic discrete time model that has exactly the Eigen model [4]as its deterministic continuous limit. Such model can be divided into two phases: reproduction, followed by neutral selection. This result suggests that Eigen’s model describes the competition among individuals differing ..."
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We exhibit a stochastic discrete time model that has exactly the Eigen model [4]as its deterministic continuous limit. Such model can be divided into two phases: reproduction, followed by neutral selection. This result suggests that Eigen’s model describes the competition among individuals
On a stochastic version of Prouse model in fluid dynamics
, 2006
"... A stochastic version of a modified Navier–Stokes equation (introduced by Prouse) is considered in a 3dimensional torus. For equation (1), we prove existence and uniqueness of martingale solutions. A different model with the non linearity Φ(u) = νu  4 u is analyzed; for the structure function of ..."
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Cited by 1 (1 self)
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A stochastic version of a modified Navier–Stokes equation (introduced by Prouse) is considered in a 3dimensional torus. For equation (1), we prove existence and uniqueness of martingale solutions. A different model with the non linearity Φ(u) = νu  4 u is analyzed; for the structure function
Results 1  10
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236,753