דיווח מומנט-מנחה: סיימפלינג של קצוות

תקציר מקורי באנגליתarXiv:2609.30472v1 Announce Type: new Abstract: Edge sampling makes local decisions to achieve graph-level objectives, such as preserving structural properties. This creates a fundamental challenge: \textit{how can the effect of a local edge edit (i.e., edge addition or removal) on global graph structure be quantified and controlled?} We address this challenge with a \textit{moment-guided edge sampling framework} based on spectral moments of the random-walk transition matrix. We compute exact moment changes through two complementary methods: a combinatorial method with closed-form updates for low-order moments, and a low-rank method that exploits \textit{locality} and \textit{cyclic trace invariance} to compress computations to edited endpoints, supporting arbitrary moment orders and batch