Loadstar: Load Shedding in Data Stream Mining

Summary: Loadstar applies adaptive load shedding to high-volume streams under resource constraints, using QoD to target high-uncertainty sources. It uses feature prediction to model shed data and adapts to changing stream traits for robust, resource-aware classification. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 9466
Venue: VLDB
Year: 2005
Pagerank: 5.093636e-05
Overall Rank: 12,748 | 12.54%
DOI: -

Incoming Non-self Citations Over Time

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Authors

1. Yun Chi (University of California Los Angeles)
2. Haixun Wang (IBM)
3. Philip S. Yu (IBM)

BibTeX Citation

@article{chi_vldb05,
        title = {{Loadstar: Load Shedding in Data Stream Mining}},
        author = {Chi, Yun and Wang, Haixun and Yu, Philip S.},
        journal = {PVLDB},
        series = {{VLDB} '05},
        pages = {1302},
        year = {2005}
}

Incoming Citations (Sorted by Pagerank)

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Rank	Citing Paper	Year	Venue	Pagerank

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
671	Load Shedding in a Data Stream Manager	2003	VLDB	0.00015154516

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