Anomaly identification with limited sampling budget
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| Publication date | 2016 |
| Book title | 2016 IEEE Information Theory Workshop (ITW 2016) |
| Book subtitle | Cambridge, United Kingdom, 11-14 September 2016 |
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| ISBN (electronic) |
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| Series | IEEE Conference Proceedings |
| Event | Information Theory Workshop (ITW 2016) |
| Pages (from-to) | 216-220 |
| Publisher | Piscataway, NJ: IEEE |
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| Abstract |
We consider a network of data streams from which an anomalous process with known target distribution is to be identified. Because in practice obtaining observations may be expensive, we assume that there is a constraint on the total number of observations based on which the decision has to be made. We derive a sufficient condition on the sampling budget such that the error probability is kept below some desired level. Furthermore, we show how to obtain a sampling allocation that can improve upon equal sampling allocation and achieves the desired accuracy. |
| Document type | Conference contribution |
| Language | English |
| Published at |
https://doi.org/10.1109/ITW.2016.7606827
(Final published version)
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