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» Advances in Mixture Models
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AAAI
2012
13 years 2 months ago
Advances in Lifted Importance Sampling
We consider lifted importance sampling (LIS), a previously proposed approximate inference algorithm for statistical relational learning (SRL) models. LIS achieves substantial vari...
Vibhav Gogate, Abhay Kumar Jha, Deepak Venugopal
ICML
2009
IEEE
16 years 29 days ago
Archipelago: nonparametric Bayesian semi-supervised learning
Semi-supervised learning (SSL), is classification where additional unlabeled data can be used to improve accuracy. Generative approaches are appealing in this situation, as a mode...
Ryan Prescott Adams, Zoubin Ghahramani
ICML
2005
IEEE
16 years 29 days ago
Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning
Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...
Xiaojin Zhu, John D. Lafferty
77
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PAMI
2008
140views more  PAMI 2008»
15 years 2 days ago
Simplifying Mixture Models Using the Unscented Transform
Mixture of Gaussians (MoG) model is a useful tool in statistical learning. In many learning processes that are based on mixture models, computational requirements are very demandin...
Jacob Goldberger, Hayit Greenspan, Jeremie Dreyfus...
NECO
2002
95views more  NECO 2002»
14 years 11 months ago
Mixture of Experts Classification Using a Hierarchical Mixture Model
Michalis K. Titsias, Aristidis Likas