Pac-bayes tree: Weighted subtrees with guarantees

Author(s): Nguyen, T; Kpotufe, S

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DC Field	Value	Language
dc.contributor.author	Nguyen, T	-
dc.contributor.author	Kpotufe, S	-
dc.date.accessioned	2021-10-11T14:17:14Z	-
dc.date.available	2021-10-11T14:17:14Z	-
dc.date.issued	2018	en_US
dc.identifier.citation	Nguyen, Tin D., and Samory Kpotufe. "PAC-Bayes Tree: weighted subtrees with guarantees." In Advances in Neural Information Processing Systems 31, pp. 9484-9492. 2018.	en_US
dc.identifier.issn	1049-5258	-
dc.identifier.uri	http://papers.nips.cc/paper/8158-pac-bayes-tree-weighted-subtrees-with-guarantees	-
dc.identifier.uri	http://arks.princeton.edu/ark:/88435/pr1s57f	-
dc.description.abstract	We present a weighted-majority classification approach over subtrees of a fixed tree, which provably achieves excess-risk of the same order as the best tree-pruning. Furthermore, the computational efficiency of pruning is maintained at both training and testing time despite having to aggregate over an exponential number of subtrees. We believe this is the first subtree aggregation approach with such guarantees.	en_US
dc.format.extent	9484 - 9492	en_US
dc.language.iso	en_US	en_US
dc.relation.ispartof	Advances in Neural Information Processing Systems	en_US
dc.rights	Final published version. Article is made available in OAR by the publisher's permission or policy.	en_US
dc.title	Pac-bayes tree: Weighted subtrees with guarantees	en_US
dc.type	Conference Article	en_US
pu.type.symplectic	http://www.symplectic.co.uk/publications/atom-terms/1.0/conference-proceeding	en_US

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