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Exact Learning of Weighted Graphs Using Composite Queries

Data Structures and Algorithms 2025-11-20 v1 Machine Learning

Abstract

In this paper, we study the exact learning problem for weighted graphs, where we are given the vertex set, VV, of a weighted graph, G=(V,E,w)G=(V,E,w), but we are not given EE. The problem, which is also known as graph reconstruction, is to determine all the edges of EE, including their weights, by asking queries about GG from an oracle. As we observe, using simple shortest-path length queries is not sufficient, in general, to learn a weighted graph. So we study a number of scenarios where it is possible to learn GG using a subquadratic number of composite queries, which combine two or three simple queries.

Keywords

Cite

@article{arxiv.2511.14882,
  title  = {Exact Learning of Weighted Graphs Using Composite Queries},
  author = {Michael T. Goodrich and Songyu Liu and Ioannis Panageas},
  journal= {arXiv preprint arXiv:2511.14882},
  year   = {2025}
}

Comments

Full version of the paper published at IWOCA 2025

R2 v1 2026-07-01T07:44:11.779Z