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Deterministic Wavelet Thresholding for Maximum-Error Metrics

Summary: Deterministic algorithms for wavelet thresholding that directly minimize maximum absolute/relative reconstruction error, avoiding the failure modes of prior probabilistic schemes. Provides an optimal low-polynomial DP for 1D and polynomial-time approximation schemes with tunable guarantees for multi-D. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1318
Venue
PODS
Year
2004
Pagerank
6.7605683e-05
Overall Rank
4,325 | 70.33%
DOI
10.1145/1055558.1055582

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{garofalakis_pods04,
        address = {New York, NY, USA},
        series = {{PODS} '04},
        title = {{Deterministic Wavelet Thresholding for Maximum-Error Metrics}},
        url = {https://dl.acm.org/doi/10.1145/1055558.1055582},
        doi = {10.1145/1055558.1055582},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Garofalakis, Minos and Kumar, Amit},
        year = {2004}
}

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