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» Structural Inference for Semistructured Data
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ESOP
2011
Springer
14 years 6 months ago
Measure Transformer Semantics for Bayesian Machine Learning
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Johannes Borgström, Andrew D. Gordon, Michael...
PLDI
2004
ACM
15 years 8 months ago
Parametric regular path queries
Regular path queries are a way of declaratively expressing queries on graphs as regular-expression-like patterns that are matched against paths in the graph. There are two kinds o...
Yanhong A. Liu, Tom Rothamel, Fuxiang Yu, Scott D....
CSDA
2006
169views more  CSDA 2006»
15 years 3 months ago
Generalized structured additive regression based on Bayesian P-splines
Generalized additive models (GAM) for modelling nonlinear effects of continuous covariates are now well established tools for the applied statistician. In this paper we develop Ba...
Andreas Brezger, Stefan Lang
JMLR
2010
125views more  JMLR 2010»
14 years 10 months ago
Continuous Time Bayesian Network Reasoning and Learning Engine
We present a continuous time Bayesian network reasoning and learning engine (CTBN-RLE). A continuous time Bayesian network (CTBN) provides a compact (factored) description of a co...
Christian R. Shelton, Yu Fan, William Lam, Joon Le...
CSDA
2006
67views more  CSDA 2006»
15 years 3 months ago
Sensitivity analysis of the strain criterion for multidimensional scaling
Multidimensional scaling (MDS) is a collection of data analytic techniques for constructing configurations of points from dissimilarity information about interpoint distances. Cla...
R. M. Lewis, M. W. Trosset