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We present a general method for maintaining estimates of the distribution of parameters in arbitrary models. This is then applied to the estimation of probability distribution over actions in value-based reinforcement learning. While this approach is simil ...
This thesis is a contribution to multivariate extreme value statistics. The tail of a multivariate distribution function is characterized by its spectral distribution, for which we propose a new semi-parametric model based on mixtures of Dirichlet distribu ...
The structural refinement of the modulated phase of 4,4'-Diethoxyazoxybenzene (DXB) indicates a correlation between the shifts on the DXB molecule (modulation) and the probability to find the azoxy (N --> O) group in different configurations (disorder). Th ...
An application to antenna optimization of bayesian network density of probability estimators is presented. This technique is very usefull for optimizations where abig number of parameters, multiple solutions and local minima increase the likelihood to conv ...
The reliability of new overhead electric and telecommunication lines depends principally on the quality of their support structures. These structures are generally made of wood, metal or concrete. The complexity of a natural substance such as wood requires ...
This paper presents a general method for incorporating prior knowledge into kernel methods such as Support Vector Machines. It applies when the prior knowledge can be formalized by the description of an object around each sample of the training set, assumi ...
This paper focuses on the statistical analysis of an adaptive real-time feedback scheduling technique based on imprecise computation. We consider two-version tasks made of a mandatory and an optional part to be scheduled according to a feedback control rat ...
Two distinct methods underlying the existence of power-law distribution were studied. The distribution ws stationary under the process of merging and splitting of classes and the distribution of the entities under study was invariant. An explanation for th ...
This paper describes a procedure based on the Monte Carlo method to obtain the statistical distributions of lightning current parameters at ground level starting from those inferred from experimental data recorded by means of tall instrumented towers. As a ...
In this paper, the design of probabilistic observers for mass-balance based bioprocess models is investigated. It is assumed that the probability density of every uncertain parameter, input and/or initial state is known a priori. Then, the probability dens ...
