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ML
2002
ACM
246views Machine Learning» more  ML 2002»
13 years 8 months ago
Bayesian Clustering by Dynamics
This paper introduces a Bayesian method for clustering dynamic processes. The method models dynamics as Markov chains and then applies an agglomerative clustering procedure to disc...
Marco Ramoni, Paola Sebastiani, Paul R. Cohen
ICASSP
2008
IEEE
14 years 3 months ago
Joint Bayesian positioning and multipath mitigation in GNSS
A sequential Bayesian estimation algorithm for joint positioning and multipath mitigation within satellite navigation receivers is presented. The underlying process model is espec...
Bernhard Krach, Michael Lentmaier, Patrick Roberts...
CSL
2007
Springer
13 years 8 months ago
Articulatory feature recognition using dynamic Bayesian networks
This paper describes the use of dynamic Bayesian networks for the task of articulatory feature recognition. We show that by modeling the dependencies between a set of 6 multi-leve...
Joe Frankel, Mirjam Wester, Simon King
NIPS
2008
13 years 10 months ago
Nonparametric Bayesian Learning of Switching Linear Dynamical Systems
Many nonlinear dynamical phenomena can be effectively modeled by a system that switches among a set of conditionally linear dynamical modes. We consider two such models: the switc...
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan,...
AAAI
1998
13 years 10 months ago
Structured Representation of Complex Stochastic Systems
This paperconsidersthe problem of representingcomplex systems that evolve stochastically over time. Dynamic Bayesian networks provide a compact representation for stochastic proce...
Nir Friedman, Daphne Koller, Avi Pfeffer