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» On Bayesian model and variable selection using MCMC
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PERCOM
2007
ACM
15 years 9 months ago
Structural Learning of Activities from Sparse Datasets
Abstract. A major challenge in pervasive computing is to learn activity patterns, such as bathing and cleaning from sensor data. Typical sensor deployments generate sparse datasets...
Fahd Albinali, Nigel Davies, Adrian Friday
EMNLP
2006
14 years 11 months ago
A Skip-Chain Conditional Random Field for Ranking Meeting Utterances by Importance
We describe a probabilistic approach to content selection for meeting summarization. We use skipchain Conditional Random Fields (CRF) to model non-local pragmatic dependencies bet...
Michel Galley
BMCBI
2010
124views more  BMCBI 2010»
14 years 10 months ago
Estimating time since infection in early homogeneous HIV-1 samples using a poisson model
Background: The occurrence of a genetic bottleneck in HIV sexual or mother-to-infant transmission has been well documented. This results in a majority of new infections being homo...
Elena E. Giorgi, Bob Funkhouser, Gayathri Athreya,...
IEAAIE
2001
Springer
15 years 2 months ago
A Knowledge Model for Automatic Configuration of Traffic Messages
: This paper describes a knowledge model for a configuration problem in the domain of traffic control. The goal of this model is to help traffic engineers in the dynamic selection ...
Martín Molina, Mónica Robledo
ICML
2004
IEEE
15 years 3 months ago
Gradient LASSO for feature selection
LASSO (Least Absolute Shrinkage and Selection Operator) is a useful tool to achieve the shrinkage and variable selection simultaneously. Since LASSO uses the L1 penalty, the optim...
Yongdai Kim, Jinseog Kim