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Bibliography

Conference Paper (international conference)

Dynamic Mixture Ratio Model

Ruman Marko, Kárný Miroslav

: Proceedings of the 2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO), p. 92-99

: The Institute of Electrical and Electronics Engineers, Inc., ( 2020)

: International Conference on Control, Artificial Intelligence, Robotics & Optimization ICCAIRO 2019, (Athens, GR, 20191208)

: LTC18075, GA MŠk, CA16228, The European Cooperation in Science and Technology (COST)

: dynamic systems, mixture models, Bayesian learning, mixture ratio

: 10.1109/ICCAIRO47923.2019.00023

: http://library.utia.cas.cz/separaty/2020/AS/karny-0524580.pdf

(eng): Finite mixtures of probability densities with components from exponential family serve as flexible parametric models of high-dimensional systems. However, with a few specialized exceptions, these dynamic models assume data-independent weights of mixture components. Their use is illogical and restricts the modeling applicability. The requirement for closeness with respect to conditioning, the basic learning operation, leads to a novel class of models: the mixture ratios. The paper justified them and shows their ability to model truly dynamic systems.

: BD

: 10201

2019-01-07 08:39