Learning-Augmented Hierarchical Clustering

Vladimir Braverman; Jon C. Ergun; Chen Wang; Samson Zhou

ICML2025Top-tier venue

Learning-Augmented Hierarchical Clustering

Vladimir Braverman, Jon C. Ergun, Chen Wang, Samson Zhou

Abstract

In this chapter, we only consider hierarchies that are binary trees like the one shown in Figure 17.1 -but hierarchical clustering can be easily extended to other types of trees.

Ask Lune

Ask anything. The answer quotes the paper.

Lune reads all of it and the papers around it, then shows you the passages behind every answer.

What it claims
Who builds on it
How it compares
Where it falls short

Your question

Lune answers from

the full paper · 6 top-tier papers that cite it · related work

Get the answer

Free to start. No credit card required.

Cited by top-tier papers6

Learning-Augmented Moment Estimation on Time-Decay ModelsSoham Nagawanshi, Shalini Panthangi, Chen Wang, David P. Woodruff et al.ICLR 2026 · 3 citations
Nearly Space-Optimal Graph and Hypergraph Sparsification in Insertion-Only Data StreamsVincent Cohen-Addad, David P. Woodruff, Shenghao Xie, Samson ZhouICLR 2026 · 2 citations
Relative Error Fair Clustering in the Weak-Strong Oracle ModelVladimir Braverman, Prathamesh Dharangutte, Shaofeng H.-C. Jiang, Hoai-An Nguyen et al.ICML 2025
Metric $k$ -clustering using only Weak Comparison OraclesRahul Raychaudhury, Aryan Esmailpour, Sainyam Galhotra, Stavros SintosICLR 2026
Universal Guideline-Driven Image Clustering via a Hybrid LLM AgentWenliang Zhong, Rob Barton, Lucas Goncalves, Kushal Kumar et al.CVPR 2026

Ask how each one uses it

Abstract

Ask Lune

Ask anything. The answer quotes the paper.

Cited by top-tier papers6

Related papers