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Uniform \emph{a priori} bounds for neutral renormalization. Variation~\RN{2}: $\psi^\bullet$-ql Siegel maps
Dzmitry Dudko, Yusheng Luo, Mikhail Lyubich
https://arxiv.org/abs/2509.23031

Uniform \emph{a priori} bounds for neutral renormalization. Variation~\RN{2}: $ψ^\bullet$-ql Siegel maps
We extend uniform pseudo-Siegel bounds for neutral quadratic polynomials to $ψ^\bullet$-quadratic-like Siegel maps. In this form, the bounds are compatible with the $ψ$-quadratic-like renormalization theory and are easily transferable to various families of rational maps. The main theorem states that the degeneration of a Siegel disk is equidistributed among combinatorial intervals. This provides a precise description of how the $ψ^\bullet$-quadratic-like structure degenerates around the Sie…

From Ethical Declarations to Provable Independence: An Ontology-Driven Optimal-Transport Framework for Certifiably Fair AI Systems
Sukriti Bhattacharya, Chitro Majumdar
https://arxiv.org/abs/2510.08086

From Ethical Declarations to Provable Independence: An Ontology-Driven Optimal-Transport Framework for Certifiably Fair AI Systems
This paper presents a framework for provably fair AI that overcomes the limits of current bias mitigation methods by systematically removing all sensitive information and its proxies. Using ontology engineering in OWL 2 QL, it formally defines sensitive attributes and infers their proxies through logical reasoning, constructing a sigma algebra G that captures the full structure of biased patterns. Fair representations are then obtained via Delbaen Majumdar optimal transport, which generates var…

Elastic Meetup #98 - Analyse de données interactive : la rencontre de ES|QL, Arrow et Pandas - YouTube
https://www.youtube.com/watch?v=O7WBydgZErI
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Crosslisted article(s) found for math.CV. https://arxiv.org/list/math.CV/new
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- Uniform \emph{a priori} bounds for neutral renormalization. Variation~\RN{2}: $\psi^\bullet$-ql S...
Dzmitry Dudko, Yusheng Luo, Mikhail Lyubich