Conveners
Stochastic Monitoring Systems
- Jiří Franc (Czech Technical University (CZ))
Stochastic Monitoring Systems
- Václav Kůs (Department of Mathematics, FNSPE Czech Technical University in Prague)
Stochastic Monitoring Systems
- Jiří Franc (Czech Technical University (CZ))
A novel extension of Independent Component Analysis for blind extraction/separation of one or several sources from time-varying mixtures is proposed. The Signals of Interest in mixtures are assumed to be dynamic, i.e., they are moving, while the other sources are static. The extension version of popular FastICA algorithm is analysed. The algorithms are derived within a unified framework so...
Blind image deconvolution aims on recovering sharp image from a blurred one while the blur is unknown. It is a highly ill-posed problem requiring suitable regularization. One of the commonly used approaches for solving this problem is variational Bayesian inference. Hierarchical Bayesian models allow for a good representation of both sharp image and blur kernel and Variational Bayes can be...
In the modern world of lots of data, there is a large number of powerful and effective tools for estimating the parameters of models, on the basis of which it is then possible to predict new values. To save valuable computational time, various types of regularizations can be added to the models to force sparse parameterization. Thanks to such parameterization, it can be aimed at better...
Stochastic models of diffusion in spatial domains of noninteger dimension are widely applicable as a basis of simulations. Obtaining data having fractal properties requires the construction of fine enough discrete latices that is computationally expensive. This contribution presents a novel way of representing graph-based finite models using a generalized coordinate system. Presented methods...
Simultaneous search for multiple sparse solutions of a classification/regression problems differs fundamentally from common approaches to these classical machine learning problems. At the same time, it is strongly motivated by practical requirements, e.g. in applications in biomedicine. In such tasks, we face high dimensions, limited number of samples, errors in data and, most importantly, the...
The theory of real option analysis (ROA) is considered as an advanced project valuation technique, which respects the value of future project alternations (real options).
To our best knowledge, the current state of ROA does not offer a unified valuation algorithm that would be able to cover valuations of more complex projects, such as those with multiple random variables or different...
Evolutionary algorithms are known to converge to non-evolving populations rather quickly. Rewarding with respect to an objective does not improve overall performance. Novelty Search is one of the solutions to this problem. We explored and developed techniques which can complement the popular divergent algorithm called Novelty Search. We believe its main drawback lies in attempting to define...
This work deals with the application of stochastic control methods for trading on power markets. It acquaints readers with the basics of the functioning of the electronic exchange and with the specifics of the energy market. This is followed by the theory of stochastic differential equations and stochastic optimal control. The objective is to understand the current results in the field of...
