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We analyze a proof of Bruck to obtain an explicit rate of asymptotic regularity for Ces\`aro means in uniformly convex Banach spaces. Our rate will only depend on a norm bound and a modulus $\eta$ of uniform convexity. One ingredient for…

Dynamical Systems · Mathematics 2022-08-11 Anton Freund , Ulrich Kohlenbach

We prove the mean ergodic theorem of von Neumann in a Hilbert-Kaplansky space. We also prove a multiparameter, modulated, subsequential and a weighted mean ergodic theorems in a Hilbert-Kaplansky space

Functional Analysis · Mathematics 2012-08-29 Farruh Shahidi , Inomjon Ganiev

Stochastic embeddings of finite metric spaces into graph-theoretic trees have proven to be a vital tool for constructing approximation algorithms in theoretical computer science. In the present work, we build out some of the basic theory of…

Functional Analysis · Mathematics 2025-03-11 Chris Gartland

This is an expository article on visual metrics on boundaries of hyperbolic metric spaces. We discuss the construction of visual metrics, quasisymmetries and their invariants, Hausdorff and conformal dimension, and constructions and…

Geometric Topology · Mathematics 2025-06-13 Emily Stark

Condensed mathematics, developed by Clausen and Scholze over the last few years, is a new way of studying the interplay between algebra and geometry. It replaces the concept of a topological space by a more sophisticated but better-behaved…

Logic · Mathematics 2024-10-24 Dagur Asgeirsson

One can describe isomorphism of two compact hyperbolic Riemann surfaces of the same genus by a measure-theoretic property: a chosen isomorphism of their fundamental groups corresponds to a homeomorphism on the boundary of the Poincar\'e…

Algebraic Geometry · Mathematics 2011-12-22 Gunther Cornelissen , Janne Kool

For any intrinsic Gromov hyperbolic space we establish a Gehring-Hayman type theorem for conformally deformed spaces. As an application, we prove that any complete intrinsic hyperbolic space with atleast two points in the Gromov boundary…

Complex Variables · Mathematics 2024-11-04 Vasudevarao Allu , Alan P Jose

Learning the representation of data with hierarchical structures in the hyperbolic space attracts increasing attention in recent years. Due to the constant negative curvature, the hyperbolic space resembles tree metrics and captures the…

Machine Learning · Computer Science 2022-02-21 Huiru Xiao , Caigao Jiang , Yangqiu Song , James Zhang , Junwu Xiong

Herbrand's theorem is one of the most fundamental insights in logic. From the syntactic point of view, it suggests a compact representation of proofs in classical first- and higher-order logic by recording the information of which instances…

Logic · Mathematics 2019-10-09 Federico Aschieri , Stefan Hetzl , Daniel Weller

We compute, using techniques originally introduced by Kohlenbach, the first author and Nicolae, uniform rates of metastability for the proximal point algorithm in the context of CAT(0) spaces (as first considered by Bacak), specifically for…

Optimization and Control · Mathematics 2017-07-31 Laurentiu Leustean , Andrei Sipos

We use techniques of proof mining to extract computable and uniform rates of metastability (in the sense of Tao) for iterations of continuous functions on the unit interval, firstly (following earlier work of Gaspar) out of convergence…

Classical Analysis and ODEs · Mathematics 2021-04-13 Andrei Sipos

We prove a geometric criterion on a $\SL$-invariant ergodic probability measure on the moduli space of holomorphic abelian differentials on Riemann surfaces for the non-uniform hyperbolicity of the Kontsevich--Zorich cocycle on the real…

Dynamical Systems · Mathematics 2011-03-25 Giovanni Forni

Kohlenbach and Leustean have shown in 2010 that any asymptotically nonexpansive self-mapping of a bounded nonempty $UCW$-hyperbolic space has a fixed point. In this paper, we adapt a construction due to Moloney in order to provide a…

Metric Geometry · Mathematics 2021-04-29 Andrei Sipos

Hyperbolic spaces, which have the capacity to embed tree structures without distortion owing to their exponential volume growth, have recently been applied to machine learning to better capture the hierarchical nature of data. In this…

Machine Learning · Computer Science 2021-03-18 Ryohei Shimizu , Yusuke Mukuta , Tatsuya Harada

We prove Penner's theorem on horocycles and theorems of Ptolemy and Casey, all with full converses, in hyperbolic space of several dimensions. Recently Waddle observed that the equations underpinning these three theorems are related, and it…

Metric Geometry · Mathematics 2026-05-25 Isabella Lewis , Ian Short

We introduce the concept of boundary rigidity for Gromov hyperbolic spaces. We show that a proper geodesic Gromov hyperbolic space with a pole is boundary rigid if and only if its Gromov boundary is uniformly perfect. As an application, we…

Geometric Topology · Mathematics 2022-09-09 Hao Liang , Qingshan Zhou

We propose a kernel-based nonparametric framework for mean-variance optimization that enables inference on economically motivated shape constraints in finance, including positivity, monotonicity, and convexity. Many central hypotheses in…

Machine Learning · Statistics 2026-01-26 Rohan Sen

Agentic theorem provers combine a reasoning model, retrieval, search, and a proof assistant verifier, yet it remains unclear which components actually improve finite-budget proof success and why they help on real mathematical workloads. We…

Machine Learning · Statistics 2026-05-26 Sho Sonoda , Shunta Akiyama , Yuya Uezato

Hierarchically hyperbolic spaces provide a common framework for studying mapping class groups of finite type surfaces, Teichm\"uller space, right-angled Artin groups, and many other cubical groups. Given such a space $\mathcal X$, we build…

Geometric Topology · Mathematics 2018-03-16 Matthew G. Durham , Mark F. Hagen , Alessandro Sisto

Hyperbolic space is quickly gaining traction as a promising geometry for hierarchical and robust representation learning. A core open challenge is the development of a mathematical formulation of hyperbolic neural networks that is both…

Machine Learning · Computer Science 2026-01-30 Robert van der Klis , Ricardo Chávez Torres , Max van Spengler , Yuhui Ding , Thomas Hofmann , Pascal Mettes