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NIPS
2001
15 years 10 days ago
Bayesian time series classification
This paper proposes an approach to classification of adjacent segments of a time series as being either of classes. We use a hierarchical model that consists of a feature extract...
Peter Sykacek, Stephen J. Roberts
PSB
2004
15 years 9 days ago
Modeling Cellular Processes with Variational Bayesian Cooperative Vector Quantizer
Gene expression of a cell is controlled by sophisticated cellular processes. The capability of inferring the states of these cellular processes would provide insight into the mech...
Xinghua Lu, Milos Hauskrecht, Roger S. Day
ML
2002
ACM
220views Machine Learning» more  ML 2002»
14 years 10 months ago
Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Peter Sollich
ICASSP
2009
IEEE
14 years 8 months ago
Spoken language interpretation: On the use of dynamic Bayesian networks for semantic composition
In the context of spoken language interpretation, this paper introduces a stochastic approach to infer and compose semantic structures. Semantic frame structures are directly deri...
Marie-Jean Meurs, Fabrice Lefevre, Renato de Mori
SIAMSC
2011
219views more  SIAMSC 2011»
14 years 5 months ago
Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian
We consider the problem of estimating the uncertainty in large-scale linear statistical inverse problems with high-dimensional parameter spaces within the framework of Bayesian inf...
H. P. Flath, Lucas C. Wilcox, Volkan Akcelik, Judi...