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ICML
2005
IEEE
14 years 9 months ago
Compact approximations to Bayesian predictive distributions
We provide a general framework for learning precise, compact, and fast representations of the Bayesian predictive distribution for a model. This framework is based on minimizing t...
Edward Snelson, Zoubin Ghahramani
CIKM
2005
Springer
14 years 2 months ago
Information retrieval and machine learning for probabilistic schema matching
Schema matching is the problem of finding correspondences (mapping rules, e.g. logical formulae) between heterogeneous schemas e.g. in the data exchange domain, or for distribute...
Henrik Nottelmann, Umberto Straccia
ICML
2001
IEEE
14 years 9 months ago
General Loss Bounds for Universal Sequence Prediction
The Bayesian framework is ideally suited for induction problems. The probability of observing xt at
Marcus Hutter
ECTEL
2009
Springer
14 years 3 months ago
SWeMoF: A Semantic Framework to Discover Patterns in Learning Networks
Marco Kalz, Niels Beekman, Anton Karsten, Diederik...
ICML
2009
IEEE
14 years 9 months ago
A scalable framework for discovering coherent co-clusters in noisy data
Meghana Deodhar, Gunjan Gupta, Joydeep Ghosh, Hyuk...