Formalizing statistical learning theory in Lean 4 [R]

Short summary

A Lean 4 formalization effort that rigorously proves core statistical learning theory results—Rademacher bounds, PAC-Bayes, VC-dimension, algorithmic stability—with explicit finite-sample analysis and pedagogical structure. The project emphasizes readable theorem chains and zero proof gaps over abstract probability infrastructure, and invites community feedback on theorem organization, naming conventions, and next formalization priorities.

• •Lean 4 formalization of SLT theorems with explicit assumptions and zero proof gaps
• •Pedagogically structured, readable theorem chains emphasizing finite-sample routes
• •Open-source project seeking community feedback on organization and future targets

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