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» Comparing the Bayes and Typicalness Frameworks
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UAI
2003
13 years 7 months ago
Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes
Collaborative filtering (CF) and contentbased filtering (CBF) have widely been used in information filtering applications, both approaches having their individual strengths and...
Kai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying...
NIPS
2008
13 years 7 months ago
Hebbian Learning of Bayes Optimal Decisions
Uncertainty is omnipresent when we perceive or interact with our environment, and the Bayesian framework provides computational methods for dealing with it. Mathematical models fo...
Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
CVPR
2011
IEEE
13 years 2 months ago
A Deformation and Lighting Insensitive Metric for Face Recognition
Face recognition is a challenging problem, complicated by variations in pose, expression, lighting, and the passage of time. Significant work has been done to solve each of these...
Anne Jorstad, David Jacobs, Alain Trouvé
JMLR
2010
136views more  JMLR 2010»
13 years 22 days ago
Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes
Variational Bayesian (VB) methods are typically only applied to models in the conjugate-exponential family using the variational Bayesian expectation maximisation (VB EM) algorith...
Antti Honkela, Tapani Raiko, Mikael Kuusela, Matti...
JCB
2008
159views more  JCB 2008»
13 years 5 months ago
BayesMD: Flexible Biological Modeling for Motif Discovery
We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fa...
Man-Hung Eric Tang, Anders Krogh, Ole Winther