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|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.|
|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.|
|Pages:||9484 - 9492|
|Type of Material:||Conference Article|
|Journal/Proceeding Title:||Advances in Neural Information Processing Systems|
|Version:||Final published version. Article is made available in OAR by the publisher's permission or policy.|
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