Data-driven coarse graining in action: Modeling and prediction of complex systems
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Query optimizers depend heavily on statistics representing column distributions to create efficient query plans. In many cases, though, statistics are outdated or non-existent, and the process of refreshing statistics is very expensive, especially for ad-h ...
Query optimizers depend heavily on statistics representing column distributions to create efficient query plans. In many cases, though, statistics are outdated or non-existent, and the process of refreshing statistics is very expensive, especially for ad-h ...
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Computing statistical measures for large databases of time series is a fundamental primitive for querying and mining time-series data [1–6]. This primitive is gaining importance with the increasing number and rapid growth of time series databases. In this ...
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Computing statistical measures for large databases of time series is a fundamental primitive for querying and mining time-series data [1]–[6]. This primitive is gaining importance with the increasing number and rapid growth of time series databases. In thi ...
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