Robust Set Reconciliation via Locality Sensitive Hashing

Summary: Combine Invertible Bloom Lookup Tables with locality-sensitive hashing to perform communication-efficient robust set reconciliation in metric spaces, improving earth mover’s distance approximation from prior O(d) to O(log n). Also introduce a new per-point closeness variant with schemes that achieve sublinear communication under mild conditions. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 1784
Venue: PODS
Year: 2019
Pagerank: 5.093636e-05
Overall Rank: 11,836 | 18.80%
DOI: 10.1145/3294052.3319690

Incoming Non-self Citations Over Time

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

Authors

1. Michael Mitzenmacher (Harvard University)
2. Tom Morgan (Google; Harvard University)

BibTeX Citation

@inproceedings{mitzenmacher_pods19,
        address = {New York, NY, USA},
        series = {{PODS} '19},
        title = {{Robust Set Reconciliation via Locality Sensitive Hashing}},
        url = {https://dl.acm.org/doi/10.1145/3294052.3319690},
        doi = {10.1145/3294052.3319690},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Mitzenmacher, Michael and Morgan, Tom},
        year = {2019}
}

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
6,220	Robust Set Reconciliation	2014	SIGMOD	5.9425753e-05
11,899	Reconciling Graphs and Sets of Sets	2018	PODS	5.093636e-05

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