On the disintegration of the stochastic majority vote: From PAC-Bayesian bounds to a self-bounding algorithm
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arXiv:2609.16803v1 Announce Type: new Abstract: Weighted majority votes are central to many successful ensemble methods. PAC-Bayesian theory provides tight generalization guarantees for such models by analyzing the expected risk of stochastic classifiers, while analyzing the risk of deterministic m…
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- 2026-09-16 04:00 · arXiv stat.ML
On the disintegration of the stochastic majority vote: From PAC-Bayesian bounds to a self-bounding algorithm