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PAC--Bayes Bounds on Quotient Parameter Spaces: Geometry-induced Implicit-Bias Priors

arXiv cs.LG · 2026-07-22 Cached

This paper proposes performing PAC-Bayesian analysis on quotient parameter spaces to remove KL contributions from parameter symmetries, and constructs a geometry-induced prior that approximates the ideal posterior-matched prior, resulting in tighter generalization bounds. Experiments on Fourier regression and Query-Key attention show significant reductions in KL divergence and certificate values.

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