HomeRun: Scalable Sparse-Spectrum Reconstruction of Aggregated Historical Data

Summary: HomeRun enables high-resolution recovery from aggregated historical reports via sparse-spectrum reconstruction. Formulated as basis pursuit with a DCT sparsifying dictionary, it enforces non-negativity and smoothness, solved by ADMM for scalable, memory-efficient disaggregation, outperforming prior methods when energy is compact. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 11637
Venue: VLDB
Year: 2018
Pagerank: 4.1945683e-05
Overall Rank: 11,726 | 18.43%
DOI: 10.14778/3236187.3236201

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Rank	Citing Paper	Year	Venue	Pagerank

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

Rank	Cited Paper	Year	Venue	Pagerank
523	Recovering Information from Summary Data	1997	VLDB	0.00021089782
1,161	Querying and Mining of Time Series Data: Experimental Comparison of Representations and Distance Measures	2008	VLDB	0.00013585236
1,241	Multi-dimensional Selectivity Estimation Using Compressed Histogram Information	1999	SIGMOD	0.00013097578
2,452	Data Fusion – Resolving Data Conflicts for Integration	2009	VLDB	8.7839322e-05
3,897	SLiMFast: Guaranteed Results for Data Fusion and Source Reliability	2017	SIGMOD	6.6554845e-05

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