On the disintegration of the stochastic majority vote: From PAC-Bayesian bounds to a self-bounding algorithm

arXiv:2609.16803 · stat.ML, cs.LG · Submitted 2026-09-15 · Read on arXiv

stat.ML, cs.LG

Submitted: 2026-09-15

Updated: 2026-09-15

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Generalization — 26× in this paper · explained in 13 episodes
• Generalization Bounds — 7× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Bayesian Framework — 2× in this paper · explained in 3 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Differential Privacy — 1× in this paper · explained in 4 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Objective Function — 1× in this paper · explained in 2 episodes
• Probably Approximately Correct — 1× in this paper

Sources

• Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

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