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The Ethereal
Partial and Exact Recovery of a Random Hypergraph from its Graph Projection
February 20, 2025 ยท The Ethereal ยท ๐ Annual Conference Computational Learning Theory
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Authors
Guy Bresler, Chenghao Guo, Yury Polyanskiy, Andrew Yao
arXiv ID
2502.14988
Category
math.CO: Combinatorics
Cross-listed
cs.IT,
math.PR,
math.ST
Citations
1
Venue
Annual Conference Computational Learning Theory
Last Checked
1 month ago
Abstract
Consider a $d$-uniform random hypergraph on $n$ vertices in which hyperedges are included iid so that the average degree is $n^ฮด$. The projection of a hypergraph is a graph on the same $n$ vertices where an edge connects two vertices if and only if they belong to some hyperedge. The goal is to reconstruct the hypergraph given its projection. An earlier work of Bresler, Guo, and Polyanskiy (COLT 2024) showed that exact recovery for $d=3$ is possible if and only if $ฮด< 2/5$. This work completely resolves the question for all values of $d$ for both exact and partial recovery and for both cases of whether multiplicity information about each edge is available or not. In addition, we show that the reconstruction fidelity undergoes an all-or-nothing transition at a threshold. In particular, this resolves all conjectures from Bresler, Guo, and Polyanskiy (COLT 2024).
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