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» On Bayesian model and variable selection using MCMC
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MICCAI
2010
Springer
14 years 8 months ago
Multi-Class Sparse Bayesian Regression for Neuroimaging Data Analysis
The use of machine learning tools is gaining popularity in neuroimaging, as it provides a sensitive assessment of the information conveyed by brain images. In particular, finding ...
Vincent Michel, Evelyn Eger, Christine Keribin, Be...
CIARP
2009
Springer
15 years 4 months ago
Analysis of the GRNs Inference by Using Tsallis Entropy and a Feature Selection Approach
Abstract. An important problem in the bioinformatics field is to understand how genes are regulated and interact through gene networks. This knowledge can be helpful for many appl...
Fabrício Martins Lopes, Evaldo A. de Olivei...
NIPS
2003
14 years 11 months ago
Hierarchical Topic Models and the Nested Chinese Restaurant Process
We address the problem of learning topic hierarchies from data. The model selection problem in this domain is daunting—which of the large collection of possible trees to use? We...
David M. Blei, Thomas L. Griffiths, Michael I. Jor...
SPLC
2010
14 years 8 months ago
Stratified Analytic Hierarchy Process: Prioritization and Selection of Software Features
Product line engineering allows for the rapid development of variants of a domain specific application by using a common set of reusable assets often known as core assets. Variabil...
Ebrahim Bagheri, Mohsen Asadi, Dragan Gasevic, Sam...
TSP
2008
99views more  TSP 2008»
14 years 9 months ago
Adaptive Polarized Waveform Design for Target Tracking Based on Sequential Bayesian Inference
Abstract--In this paper, we develop an adaptive waveform design method for target tracking under a framework of sequential Bayesian inference. We employ polarization diversity to i...
Martin Hurtado, Tong Zhao, Arye Nehorai