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

Blog — PlanetScale
Blog — PlanetScale
J
Java Code Geeks
N
Netflix TechBlog - Medium
Martin Fowler
Martin Fowler
A
About on SuperTechFans
腾讯CDC
B
Blog RSS Feed
H
Hackread – Cybersecurity News, Data Breaches, AI and More
Microsoft Azure Blog
Microsoft Azure Blog
D
Docker
Y
Y Combinator Blog
Microsoft Security Blog
Microsoft Security Blog
F
Fortinet All Blogs
I
InfoQ
博客园 - 【当耐特】
美团技术团队
GbyAI
GbyAI
量子位
宝玉的分享
宝玉的分享
爱范儿
爱范儿
有赞技术团队
有赞技术团队
博客园 - Franky
L
LangChain Blog
阮一峰的网络日志
阮一峰的网络日志

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
On sequences of martingales with jumps on Riemannian subm...
[Submitted on 25 Sep 2024 (v1), last revised 3 Sep 2026 (this ve · 2024-09-26 · via math updates on arXiv.org

View PDF HTML (experimental)

Abstract:In this article, we investigate sequences of discontinuous martingales on submanifolds of higher-dimensional Euclidean space. Those sequences naturally arise when we deal with a sequence of harmonic maps with respect to non-local Dirichlet forms, such as fractional harmonic maps. We prove that the semimartingale topology is equivalent to the topology of locally uniform convergence in probability on the space of discontinuous martingales on manifolds with bounded jumps. In particular, we show that the limit of any sequence of discontinuous martingales on a compact Riemannian manifold, with respect to the topology of locally uniform convergence in probability, is a martingale on the manifold. As an application, we prove that for sequences of quasi-harmonic maps on an open set with respect to a non-local Dirichlet form, local $L^{\infty}$-convergence in the open set with pointwise convergence q.e. on the whole space implies strong local convergence in the Dirichlet space and the limit preserves harmonicity.

Submission history

From: Fumiya Okazaki [view email]
[v1] Wed, 25 Sep 2024 17:29:14 UTC (17 KB)
[v2] Thu, 3 Sep 2026 03:30:54 UTC (28 KB)