惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Last Week in AI
Last Week in AI
D
DataBreaches.Net
腾讯CDC
Recent Announcements
Recent Announcements
有赞技术团队
有赞技术团队
A
About on SuperTechFans
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
Google DeepMind News
Google DeepMind News
Microsoft Security Blog
Microsoft Security Blog
云风的 BLOG
云风的 BLOG
罗磊的独立博客
月光博客
月光博客
MyScale Blog
MyScale Blog
U
Unit 42
Martin Fowler
Martin Fowler
Stack Overflow Blog
Stack Overflow Blog
T
Tailwind CSS Blog
Engineering at Meta
Engineering at Meta
N
Netflix TechBlog - Medium
G
Google Developers Blog
博客园 - 【当耐特】
D
Docker
I
InfoQ
雷峰网
雷峰网

math updates on arXiv.org

Coupling-Robust Accuracy in Multiphysics Physics Informed Neural Networks via Kronecker-Preconditioned Optimization Non-normal spectral signatures of instability in neural network training dynamics Optimization of randomized neural networks for transfer operator approximation Selective Ambulance Dispatch Under Contextual Travel-Time Uncertainty LLAMA LIMA: A Living Meta-Analysis on the Effects of Generative AI on Learning Mathematics Neural Flow Operators can Approximate any Operator: Abstract Frameworks and Universal Approximations LLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws On the Stability of Spherical Hellinger-Kantorovich Flows and Their Implications for Differential Privacy Training-Free Looped Transformers Move on Muon : A Hamiltonian probability gradient flow perspective of Muon optimizer Entrywise Error Bounds for Spectral Ranking with Semi-Random Adversaries Asymmetric Scaling Laws from Sparse Features Is Dimensionality a Barrier for Retrieval Models? RA-DCA: A Randomized Active-Set DCA for Directional Stationarity in Max-Structured DC Programs Commutator-Induced Uncertainty in VAEs Weisfeiler-Leman Is Incomplete on Simple Spectrum Graphs, so Canonicalize Them Sparse In-Network Learning via Shortest-Path Backpropagation and Finite-Rate Gating Instance-Optimal Estimation with Multiple LLM Judges on a Budget Entropy Equivalence Testing Expand More, Shrink Less: Shaping Effective-Rank Dynamics for Dense Scaling in Recommendation Any-Dimensional Invariant Universality Operationalizing Individual Fairness via Gradient Descent and Bradley-Terry Models Anytime Training with Schedule-Free Spectral Optimization Diffusion-based Denoising Beats Vanilla Score Matching in Parameter Estimation: A Theoretical Explanation Resilience Characterization of AI-Native Wireless Receivers via Persistent Homology The General Theory of Localization Methods Group-Algebraic Tensors: Provably-optimal Equivariant Learning and Physical Symmetry Discovery General Lower Bounds for Differentially Private Federated Learning with Arbitrary Public-Transcript Interactions PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Proximal basin hopping: global optimization with guarantees
Concordance, symmetrization and non-exchangeability for b...
[Submitted on 6 May 2026 (v1), last revised 30 Jun 2026 (this ve · 2026-05-07 · via math updates on arXiv.org

This paper has been withdrawn by Manuel Úbeda-Flores

No PDF available, click to view other formats

Abstract:We study the relationship between measures of non-exchangeability $\mu_p$ ($p\in[1,+\infty]$), in the sense of Durante et al. (2010), and classical dependence functionals for bivariate copulas. We show that the symmetrization $C\mapsto(C+C^t)/2$ preserves Spearman's $\rho$ while annihilating $\mu_p$, and that Blomqvist's $\beta$ carries no information about the degree of non-exchangeability. We also establish the sharp lower bound $\sigma(C)\ge 6\,\mu_1(C)$, where $\sigma$ is the Schweizer-Wolff dependence measure, showing that asymmetry implies dependence. Closed-form expressions for $\tau$, $\rho$, and the tail-dependence coefficients of the maximally non-exchangeable family $\{M_\theta\}$ are derived as illustrations.

Submission history

From: Manuel Úbeda-Flores [view email]
[v1] Wed, 6 May 2026 17:40:26 UTC (9 KB)
[v2] Tue, 30 Jun 2026 08:10:47 UTC (1 KB) (withdrawn)