Showing stat.MLShow all
3 papers · 1 filter
stat.ML2025
Asymptotically perfect seeded graph matching without edge correlation (and applications to inference)
Tong Qi, Vera Andersson, Peter Viechnicki +1
We present the OmniMatch algorithm for seeded multiple graph matching. In the setting of -dimensional Random Dot Product Graphs (RDPG), we prove that under mild assumptions, Omn…
stat.ML2024
Optimizing the Induced Correlation in Omnibus Joint Graph Embeddings
Konstantinos Pantazis, Michael Trosset, William N. Frost +2
Theoretical and empirical evidence suggests that joint graph embedding algorithms induce correlation across the networks in the embedding space. In the Omnibus joint graph embeddin…
stat.ML2024
Gotta match 'em all: Solution diversification in graph matching matched filters
Zhirui Li, Ben Johnson, Daniel L. Sussman +2
We present a novel approach for finding multiple noisily embedded template graphs in a very large background graph. Our method builds upon the graph-matching-matched-filter techniq…