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CORR
2010
Springer
160views Education» more  CORR 2010»
13 years 7 months ago
Scalable Probabilistic Databases with Factor Graphs and MCMC
Incorporating probabilities into the semantics of incomplete databases has posed many challenges, forcing systems to sacrifice modeling power, scalability, or treatment of relatio...
Michael L. Wick, Andrew McCallum, Gerome Miklau
CSDA
2007
87views more  CSDA 2007»
13 years 7 months ago
Estimation and inference in functional mixed-effects models
Functional mixed-effects models are very useful in analyzing functional data. A general functional mixed-effects model that inherits the flexibility of linear mixed-effects model...
Anestis Antoniadis, Theofanis Sapatinas
TSP
2011
230views more  TSP 2011»
13 years 2 months ago
Bayesian Nonparametric Inference of Switching Dynamic Linear Models
—Many complex 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,...
JCB
2002
160views more  JCB 2002»
13 years 7 months ago
Inference from Clustering with Application to Gene-Expression Microarrays
There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different u...
Edward R. Dougherty, Junior Barrera, Marcel Brun, ...
ACCV
2007
Springer
14 years 1 months ago
Coarse-to-Fine Statistical Shape Model by Bayesian Inference
In this paper, we take a predefined geometry shape as a constraint for accurate shape alignment. A shape model is divided in two parts: fixed shape and active shape. The fixed shap...
Ran He, Stan Z. Li, Zhen Lei, ShengCai Liao