
Sequential Multihypothesis Testing in Multiarmed Bandit Problems:An Approach for Asymptotic Optimality
We consider a multihypothesis testing problem involving a Karmed bandi...
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Searching for Anomalies over Composite Hypotheses
The problem of detecting anomalies in multiple processes is considered. ...
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Optimal Odd Arm Identification with Fixed Confidence
The problem of detecting an odd arm from a set of K arms of a multiarme...
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Bandit Quickest Changepoint Detection
Detecting abrupt changes in temporal behavior patterns is of interest in...
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Anomaly Search with Multiple Plays under Delay and Switching Costs
The problem of searching for L anomalous processes among M processes is ...
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Bayesian sequential composite hypothesis testing in discrete time
We study the sequential testing problem of two alternative hypotheses re...
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Approximation Algorithms for Active Sequential Hypothesis Testing
In the problem of active sequential hypotheses testing (ASHT), a learner...
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Sequential Controlled Sensing for Composite Multihypothesis Testing
The problem of multihypothesis testing with controlled sensing of observations is considered. The distribution of observations collected under each control is assumed to follow a singleparameter exponential family distribution. The goal is to design a policy to find the true hypothesis with minimum expected delay while ensuring that the probability of error is below a given constraint. The decisionmaker can control the delay by intelligently choosing the control for observation collection in each time slot. We derive a policy that satisfies the given constraint on the error probability. We also show that the policy is asymptotically optimal in the sense that it asymptotically achieves an informationtheoretic lower bound on the expected delay.
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