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KDD
2004
ACM
237views Data Mining» more  KDD 2004»
15 years 10 months ago
Bayesian Model-Averaging in Unsupervised Learning From Microarray Data
Unsupervised identification of patterns in microarray data has been a productive approach to uncovering relationships between genes and the biological process in which they are in...
Mario Medvedovic, Junhai Guo
ICASSP
2009
IEEE
15 years 4 months ago
On the use of Bayesian modeling for predicting noise reduction performance
In speech enhancement applications, a validated metric of noise reduction performance is vital in the relative ranking of noise reduction algorithms and in enhancing the performan...
Nazanin Pourmand, David Suelzle, Vijay Parsa, Yi H...
CSDA
2008
77views more  CSDA 2008»
14 years 10 months ago
Maximizing equity market sector predictability in a Bayesian time-varying parameter model
A large body of evidence has emerged in recent studies confirming that macroeconomic factors play an important role in determining investor risk premia and the ultimate path of eq...
Lorne D. Johnson, Georgios Sakoulis
KDD
2008
ACM
183views Data Mining» more  KDD 2008»
15 years 10 months ago
A bayesian mixture model with linear regression mixing proportions
Classic mixture models assume that the prevalence of the various mixture components is fixed and does not vary over time. This presents problems for applications where the goal is...
Xiuyao Song, Chris Jermaine, Sanjay Ranka, John Gu...
ICPR
2010
IEEE
15 years 5 months ago
Bayesian Inference for Nonnegative Matrix Factor Deconvolution Models
In this paper we develop a probabilistic interpretation and a full Bayesian inference for non-negative matrix deconvolution (NMFD) model. Our ultimate goal is unsupervised extract...
Serap Kirbiz, Ali Taylan Cemgil, Bilge Gunsel