[PDF] Top 20 A Comparison of Algorithms for Maximum Entropy Parameter Estimation

... Third, the prediction accuracy is, in most cases, more or less the same for all of the algorithms. Some variability is to be expected—all of the data sets being considered here are badly ill-conditioned, and many ... See full document

... In this article we will present a method simplifying 3D point clouds. This method is based on the Shannon entropy. This technique of simplification is a hybrid technique where we use the notion of clustering and ... See full document

... Abstract—In this paper, direction of arrival (DOA) algorithms for Frequency Modulated (FM) point source have been implemented over a real time system. The source was a commercial FM radio station broadcasting at ... See full document

... In this case the deployment is heterogeneous i.e. all the sensors have the different range of communication as shown we accept the dimensions of the monitoring field F then we accept the maximum range of sensor ... See full document

... of maximum power points tracking techniques may ...the algorithms based on fuzzy logic and the ones using a neural network ...the maximum power poses as a major ... See full document

... the comparison for the convergence of estimated τ values for mentioned ...the comparison of fitness values for GA, PSO and PSO BFGS algorithms ...the estimation of time constant (τ), it can be ... See full document

... the estimation or identification of material parameters given measurements of the material ...identification algorithms for use in industrial, aeronautic and aerospace appli- ...the parameter ... See full document

... optimum estimation performance but with larger threshold SNR ...erent algorithms, a comparison is provided in Table ...convex algorithms is ... See full document

... the maximum likelihood estimation in the ...relative entropy in the primal objective by an arbitrary Bregman or Csisz ´ar divergence along the lines of Altun and Smola (2006), and Collins, Schapire, ... See full document

... game, the equilibrium conditions (specifically sub-game perfection) contain logical connec- tions between the endogenous variables. The resulting constrained optimization problem can be viewed as a mixed-integer ... See full document

... variances estimation, Phien provided the formulas for calculating the approximate variances and covariances of the parameter estimators and the approximate variance of the T- year event obtained by POME for ... See full document

... We develop a two-layer strategy for joint optimization over channel and data by combining the GA with the VA. At the top layer, an efficient version of GA known as the micro-GA (GA) [15] searches the channel ... See full document

... genetic algorithms for parameter estimation of non-linear eco- nomic ...genetic algorithms to estimate of parameters of demand function for durable goods and simultaneously search for ... See full document

... post-processing algorithms, also known as classifiers, are investigated to improve the performance of Google’s voice recognition system: bag-of- sentences, support vector machine, and maximum ...evaluation. ... See full document

... for maximum likelihood (ML) parameter estimation in latent variable ...gradient algorithms such as the Expectation- Maximization (EM) algorithm and its Monte Carlo ... See full document

... Statistical entropy deals with a measure of uncertainty or disorder associated with a probability ...of maximum entropy (ME) is a tool for infer- ence under uncertainty ...information entropy ... See full document

... the maximum entropy subject to finite moment constraints can be approximated by using duality of convex ...the maximum entropy principle with generalized regularization measures, that as a ... See full document

... As Chiou and Walker point out, using a larger number of draws unmasks empirical underidentification: while the best conventional solution displays acceptable convergence diagnostics at 5[r] ... See full document

... The standard approach to maximizing the simulated log-likelihood function is to use a gradient-based method such as the Newton–Raphson or Broyden–Fletcher–Goldfarb–Shanno algorithms. See Train (2009), pages ... See full document

... of entropy was first used by Rudolf Clausius in the field of thermodynamics to study the relationship between energy and temperature, the Shannon entropy [34] has a much broader scope dealing with the ... See full document