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NIPS
2003
13 years 10 months ago
Model Uncertainty in Classical Conditioning
We develop a framework based on Bayesian model averaging to explain how animals cope with uncertainty about contingencies in classical conditioning experiments. Traditional accoun...
Aaron C. Courville, Nathaniel D. Daw, Geoffrey J. ...
NIPS
2000
13 years 10 months ago
Automatic Choice of Dimensionality for PCA
A central issue in principal component analysis (PCA) is choosing the number of principal components to be retained. By interpreting PCA as density estimation, this paper shows ho...
Thomas P. Minka
IJCAI
1997
13 years 10 months ago
Probabilistic Partial Evaluation: Exploiting Rule Structure in Probabilistic Inference
Bayesian belief networks have grown to prominence because they provide compact representations of many domains, and there are algorithms to exploit this compactness. The next step...
David Poole
CACM
2011
120views more  CACM 2011»
13 years 4 months ago
The sequence memoizer
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
Frank Wood, Jan Gasthaus, Cédric Archambeau...
IJCAI
2007
13 years 10 months ago
Representations for Action Selection Learning from Real-Time Observation of Task Experts
The association of perception and action is key to learning by observation in general, and to programlevel task imitation in particular. The question is how to structure this info...
Mark A. Wood, Joanna Bryson