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» Bayesian learning of measurement and structural models
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Publication
252views
15 years 3 months ago
Context models on sequences of covers
We present a class of models that, via a simple construction, enables exact, incremental, non-parametric, polynomial-time, Bayesian inference of conditional measures. The approac...
Christos Dimitrakakis
RECOMB
2000
Springer
15 years 3 months ago
Using Bayesian networks to analyze expression data
DNA hybridization arrays simultaneously measure the expression level for thousands of genes. These measurements provide a "snapshot" of transcription levels within the c...
Nir Friedman, Michal Linial, Iftach Nachman, Dana ...
ICRA
2008
IEEE
150views Robotics» more  ICRA 2008»
15 years 6 months ago
Rigorously Bayesian range finder sensor model for dynamic environments
— This paper proposes and experimentally validates a Bayesian network model of a range finder adapted to dynamic environments. The modeling rigorously explains all model assumpt...
Tinne De Laet, Joris De Schutter, Herman Bruyninck...
ACL
2008
15 years 1 months ago
Using Adaptor Grammars to Identify Synergies in the Unsupervised Acquisition of Linguistic Structure
Adaptor grammars (Johnson et al., 2007b) are a non-parametric Bayesian extension of Probabilistic Context-Free Grammars (PCFGs) which in effect learn the probabilities of entire s...
Mark Johnson
ICML
2010
IEEE
15 years 29 days ago
Bayesian Multi-Task Reinforcement Learning
We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
Alessandro Lazaric, Mohammad Ghavamzadeh