Develops a sub-Weibull tail-aware information-theoretic framework yielding PAC-Bayes and chaining generalization bounds for RLHF and SGLD under heavy-tailed data.
Using standard trigonometry, the objective can be written as Xϕ =Z 1 cosϕ+Z 2 sinϕ=‖Z‖ 2 cos(ϕ−θ Z)
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Tail-Aware Information-Theoretic Generalization for RLHF and SGLD
Develops a sub-Weibull tail-aware information-theoretic framework yielding PAC-Bayes and chaining generalization bounds for RLHF and SGLD under heavy-tailed data.