The Gibbs–Rand Model

Summary: Proposes the first Gibbs-like generative model for clustering ensembles: probability ∝ exp(−scale · scaled Rand distance) around a center clustering. Provides poly-time sampling for constant-k centers and reconstruction for small scale, revealing richer combinatorics than the Mallows model. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 1896
Venue: PODS
Year: 2022
Pagerank: 5.093636e-05
Overall Rank: 11,530 | 20.90%
DOI: 10.1145/3517804.3526227

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

1. Flavio Chierichetti (Sapienza University)
2. Ravi Kumar (Google)
3. Silvio Lattanzi (Google)

BibTeX Citation

@inproceedings{chierichetti_pods22,
        address = {New York, NY, USA},
        series = {{PODS} '22},
        title = {{The Gibbs–Rand Model}},
        url = {https://dl.acm.org/doi/10.1145/3517804.3526227},
        doi = {10.1145/3517804.3526227},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Chierichetti, Flavio and Kumar, Ravi and Lattanzi, Silvio},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
2,644	A Model-based Approach to Attributed Graph Clustering	2012	SIGMOD	8.3043854e-05
3,234	RP-DBSCAN: A Superfast Parallel DBSCAN Algorithm Based on Random Partitioning	2018	SIGMOD	7.6144184e-05
8,739	Biclustering and Boolean Matrix Factorization in Data Streams	2020	VLDB	5.3766157e-05
8,743	A Query Engine for Probabilistic Preferences	2018	SIGMOD	5.3766157e-05
8,744	On Asymptotic Cost of Triangle Listing in Random Graphs	2017	PODS	5.3766157e-05
8,745	Querying Probabilistic Preferences in Databases	2017	PODS	5.3766157e-05
8,751	Advancing Data Clustering via Projective Clustering Ensembles	2011	SIGMOD	5.3766157e-05

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