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12

ICML
2010
IEEE

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Learning Programs: A Hierarchical Bayesian Approach

13 years 5 months ago

Learning Programs: A Hierarchical Bayesian Approach

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We are interested in learning programs for multiple related tasks given only a few training examples per task. Since the program for a single task is underdetermined by its data, we introduce a nonparametric hierarchical Bayesian prior over programs which shares statistical strength across multiple tasks. The key challenge is to parametrize this multi-task sharing. For this, we introduce a new representation of programs based on combinatory logic and provide an MCMC algorithm that can perform safe program transformations on this representation to reveal shared inter-program substructures.

Percy Liang, Michael I. Jordan, Dan Klein

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ICML 2010 | Machine Learning | Multiple Related Tasks | Multiple Tasks | Shares Statistical Strength |

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Added	09 Nov 2010
Updated	09 Nov 2010
Type	Conference
Year	2010
Where	ICML
Authors	Percy Liang, Michael I. Jordan, Dan Klein

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