82 search results - page 9 / 17 » Learning Programs: A Hierarchical Bayesian Approach |
CSDA
2006
13 years 7 months ago
2006
Fitting of non-Gaussian hierarchical random effects models by approximate maximum likelihood can be made automatic to the same extent that Bayesian model fitting can be automated ...
JMLR
2012
11 years 9 months ago
2012
The expectation maximization (EM) algorithm is a popular algorithm for parameter estimation in models with hidden variables. However, the algorithm has several non-trivial limitat...
SDM
2007
SIAM
13 years 8 months ago
2007
SIAM
We consider a novel problem of learning an optimal matching, in an online fashion, between two feature spaces that are organized as taxonomies. We formulate this as a multi-armed ...
TSP
2011
13 years 2 months ago
2011
—Many complex dynamical phenomena can be effectively modeled by a system that switches among a set of conditionally linear dynamical modes. We consider two such models: the switc...
PKDD
2010
Springer
13 years 5 months ago
2010
Springer
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...