Bandit Quickest Changepoint Detection

Gopalan, A and Lakshminarayanan, B and Saligrama, V (2021) Bandit Quickest Changepoint Detection. In: 35th Conference on Neural Information Processing Systems, NeurIPS 2021, 6 - 14 December 2021, Virtual, Online, pp. 29064-29073.

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Abstract

Many industrial and security applications employ a suite of sensors for detecting abrupt changes in temporal behavior patterns. These abrupt changes typically manifest locally, rendering only a small subset of sensors informative. Continuous monitoring of every sensor can be expensive due to resource constraints, and serves as a motivation for the bandit quickest changepoint detection problem, where sensing actions (or sensors) are sequentially chosen, and only measurements corresponding to chosen actions are observed. We derive an information-theoretic lower bound on the detection delay for a general class of finitely parameterized probability distributions. We then propose a computationally efficient online sensing scheme, which seamlessly balances the need for exploration of different sensing options with exploitation of querying informative actions. We derive expected delay bounds for the proposed scheme and show that these bounds match our information-theoretic lower bounds at low false alarm rates, establishing optimality of the proposed method. We then perform a number of experiments on synthetic and real datasets demonstrating the effectiveness of our proposed method.

Item Type:	Conference Paper
Publication:	Advances in Neural Information Processing Systems
Publisher:	Neural information processing systems foundation
Additional Information:	The copyright for this article belongs to the Neural information processing systems foundation.
Keywords:	Behaviour patterns; Change-point detection problems; Continuous monitoring; Detection delays; General class; Information-theoretic lower bounds; Quickest changepoint detection; Resource Constraint; Security application; Temporal behavior, Probability distributions
Department/Centre:	Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited:	27 Jun 2022 07:23
Last Modified:	27 Jun 2022 07:23
URI:	https://eprints.iisc.ac.in/id/eprint/73993

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