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Keita Iwabuchi

2 accepted papers

2026

Better Learning-Augmented Spanning Tree Algorithms via Metric Forest Completion

ICLR 2026poster

We present improved learning-augmented algorithms for finding an approximate minimum spanning tree (MST) for points in an arbitrary metric space. Our work follows a recent framework called metric forest completion (MFC), where the learned input is a forest that must be given additional edges to form…

Cited by 0SourcecodeScholar
2025

Approximate Forest Completion and Learning-Augmented Algorithms for Metric Minimum Spanning Trees

ICML 2025poster

Finding a minimum spanning tree (MST) for $n$ points in an arbitrary metric space is a fundamental primitive for hierarchical clustering and many other ML tasks, but this takes $\Omega(n^2)$ time to even approximate. We introduce a framework for metric MSTs that first (1) finds a forest of trees usi…

Cited by 1SourcePDFScholar