Information Complexity: a Tutorial

Summary: Tutorial on the information-complexity paradigm for proving tight lower bounds in streaming, sketching, sampling and related massive-data models, formalizing how much information about inputs any algorithm must transmit or retain. Connects information theory, statistics, and geometry. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 1515
Venue: PODS
Year: 2010
Pagerank: 5.8056405e-05
Overall Rank: 6,677 | 54.20%
DOI: 10.1145/1807085.1807108

Incoming Non-self Citations Over Time

Authors

1. T.S. Jayram (IBM)

BibTeX Citation

@inproceedings{jayram_pods10,
        address = {New York, NY, USA},
        series = {{PODS} '10},
        title = {{Information Complexity: a Tutorial}},
        url = {https://dl.acm.org/doi/10.1145/1807085.1807108},
        doi = {10.1145/1807085.1807108},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Jayram, T.S.},
        year = {2010}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
3,795	Is Min-Wise Hashing Optimal for Summarizing Set Intersection?	2014	PODS	7.1200458e-05

Outgoing Citations (Sorted by Pagerank)

Showing 1 of 1 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
2,013	Space Efficient Mining of Multigraph Streams	2005	PODS	9.3068345e-05

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