Bibliografie
GP14-06678P
- : Factorized Estimation of Partially Shared Parameters in Diffusion Networks , IEEE Transactions on Signal Processing vol.65, 19 (2017), p. 5153-5163 [2017] Download DOI: 10.1109/TSP.2017.2725226
- : Sequential estimation and diffusion of information over networks: A Bayesian approach with exponential family of distributions , IEEE Transactions on Signal Processing vol.65, 7 (2017), p. 1795-1809 [2017] Download DOI: 10.1109/TSP.2016.2641380
- : Adaptive kernels in approximate filtering of state-space models , International Journal of Adaptive Control and Signal Processing vol.31, 6 (2017), p. 938-952 [2017] Download DOI: 10.1002/acs.2739
- : Sequential Estimation of Mixtures in Diffusion Networks , IEEE Signal Processing Letters vol.22, 2 (2015), p. 197-201 [2015] Download DOI: 10.1109/LSP.2014.2353652
- : Likelihood tempering in dynamic model averaging , Bayesian Statistics in Action, p. 67-77 , Eds: Argiento R., Lanzarone E., Villalobos I. A., Mattei A., Bayesian Young Statisticians Meeting, BAYSM 2016, (Florence, IT, 20160619) [2017] Download DOI: 10.1007/978-3-319-54084-9_7
- : Bayesian estimation of unknown parameters over networks , Proc. 2016 24th European Signal Processing Conference (EUSIPCO), p. 1508-1512, 24th European Signal Processing Conference (EUSIPCO), (Budapest, HU, 29.08.2016-02.09.2016) [2016] Download DOI: 10.1109/EUSIPCO.2016.7760500
- : Diffusion estimation of mixture models with local and global parameters , Proceedings of the 2016 IEEE Workshop on Statistical Signal Processing, p. 362-366, 2016 IEEE Statistical Signal Processing Workshop, (Palma de Mallorca, ES, 26.06.2016-29.06.2016) [2016] Download DOI: 10.1109/SSP.2016.7551775
- : Adaptive approximate filtering of state-space models , Proceedings of 23rd European Signal Processing Conference, p. 2236-2240, 23rd European Signal Processing Conference (EUSIPCO), (Nice, FR, 31.08.2015-04.09.2015) [2015] Download DOI: 10.1109/EUSIPCO.2015.7362773
- : Distributed estimation of mixture models , Bayesian statistics from methods to models and applications, p. 27-36 , Eds: Frühwirth-Schnatter S., Bitto A., Kastner G., Posekany A., Bayesian Young Statisticians Meeting (BAYSM 2014) /2./, (Vienna, AT, 18.09.2014-19.09.2014) [2015] Download DOI: 10.1007/978-3-319-16238-6_3
- : Diffusion filtration with approximate Bayesian computation , Proceedings of 2015 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), p. 3207-3211, 2015 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2015), (Brisbane, AU, 19.05.2015-24.05.2015) [2015] Download DOI: 10.1109/ICASSP.2015.7178563
- : Information fusion with functional Bregman divergence, ÚTIA AV ČR, (Praha 2015) Research Report 2345 [2015] Download
- : Diffusion Estimation Of State-Space Models: Bayesian Formulation , Proceedings of the 24th IEEE International Workshop on Machine Learning for Signal Processing (MLSP2014), The 24th IEEE International Workshop on Machine Learning for Signal Processing (MLSP2014), (Reims, FR, 21.09.2014-24.09.2014) [2014] Download DOI: 10.1109/MLSP.2014.6958920
- : Collaborative Kalman Filtration: Bayesian Perspective , Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO), p. 468-474, 11th International Conference on Informatics in Control, Automation and Robotics - ICINCO 2014, (Vien, AT, 01.09.2014-03.09.2014) [2014] Download
- : Distributed Modelling of Big Dynamic Data with Generalized Linear Models , Proceedings of the 17th International Conference on Information Fusion (Fusion 2014), 17th International Conference on Information Fusion (Fusion 2014), (Salamanca, ES, 07.07.2014-10.07.2014) [2014] Download