Plato: Approximate Analytics over Compressed Time Series with Tight Deterministic Error Guarantees
Summary: Plato provides fast approximate analytics on compressed time series with tight deterministic error guarantees for linear algebra operators (inner product, correlations). Offline: segment time series, compress each segment with a user-chosen function family, and attach 1–3 error measures; Online: compute guaranteed bounds for correlation-like queries. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Chunbin Lin (Amazon)
- 2. Etienne Boursier (Ecole normale superieure Paris-Saclay)
- 3. Yannis Papakonstantinou (Amazon; University of California San Diego)
BibTeX Citation
@article{lin_vldb20,
title = {{Plato: Approximate Analytics over Compressed Time Series with Tight Deterministic Error Guarantees}},
author = {Lin, Chunbin and Boursier, Etienne and Papakonstantinou, Yannis},
journal = {PVLDB},
series = {{VLDB} '20},
volume = {13},
number = {7},
pages = {1105--1118},
doi = {10.14778/3384345.3384357},
url = {https://doi.org/10.14778/3384345.3384357},
year = {2020}
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