Bandit Change-Point Detection for Real-Time Monitoring High-Dimensional Data Under Sampling Control

@article{Zhang2022BanditCD,
  title={Bandit Change-Point Detection for Real-Time Monitoring High-Dimensional Data Under Sampling Control},
  author={Wanrong Zhang and Yajun Mei},
  journal={Technometrics},
  year={2022}
}
In many real-world problems of real-time monitoring high-dimensional streaming data, one wants to detect an undesired event or change quickly once it occurs, but under the sampling control constraint in the sense that one might be able to only observe or use selected components data for decision-making per time step in the resource-constrained environments. In this paper, we propose to incorporate multi-armed bandit approaches into sequential change-point detection to develop an efficient… 

Figures and Tables from this paper

Adaptive Partially Observed Sequential Change Detection and Isolation

This work focuses on the online adaptive monitoring of high-dimensional data in resource-constrained environments with multiple potential failure modes and proposes to apply the Shiryaev–Roberts procedure on the failure mode level and use the multi-arm bandit to balance the exploration and exploitation.

A Generic Online Nonparametric Monitoring and Sampling Strategy for High-Dimensional Heterogeneous Processes

  • Honghan YeKaibo Liu
  • Computer Science
    IEEE Transactions on Automation Science and Engineering
  • 2022
A generic online nonparametric monitoring and sampling scheme to quickly detect mean shifts occurring in heterogeneous processes when only partial observations are available at each acquisition time is proposed and has much better performance than the existing methods in reducing detection delay and effectively dealing with heterogeneous data streams.

Adaptive Resources Allocation CUSUM for Binomial Count Data Monitoring with Application to COVID-19 Hotspot Detection

An efficient statistical method to robustly and efficiently detect the hotspot with limited sampling resources to balance the exploration and exploitation of resource allocation for hotspot detection is presented.

Quickest Change Detection with Controlled Sensing

In the problem of quickest change detection, a change occurs at some unknown time in the distribution of a sequence of random vectors that are monitored in real time, and the goal is to detect this

In-process quality improvement: Concepts, methodologies, and applications

Abstract This article presents the concepts, methodologies, and applications of In-Process Quality Improvement (IPQI) in complex manufacturing systems. As opposed to traditional quality control

Surveillance for endemic infectious disease outbreaks: Adaptive sampling using profile likelihood estimation

An adaptive sampling algorithm that uses profile likelihood to estimate the distribution of the number of positive tests that would occur for each location in a future time period if that location were sampled and provides an effective and reliable method for rapidly detecting endemic disease outbreaks.

Bandit Quickest Changepoint Detection

This work derives an information-theoretic lower bound on the detection delay for a general class ofitely parameterized probability distributions and proposes a computationally efficient online sensing scheme, which seamlessly balances the need for exploration of different sensing options with exploitation of querying informative actions.

References

SHOWING 1-10 OF 56 REFERENCES

A Comparison of Some Control Chart Procedures

This paper unifies and extends previously published characterizations of moving average, geometric moving average, and cumulative sum control chart procedures. It presents comparable

A two-stage online monitoring procedure for high-dimensional data streams

  • Jun Yu Li
  • Computer Science
    Journal of Quality Technology
  • 2018
A two-stage monitoring procedure is proposed to control both the IC-ARL and Type-I errors at the levels specified by users, allowing users to choose not only how often they expect any false alarms when all data streams are IC but also how many false alarms they can tolerate when identifying abnormal data streams.

Multisensor Data Fusion for Next Generation Distributed Intrusion Detection Systems

This paper provides a few steps toward developing the engineering requirements using the art and science of multisensor data fusion as the underlying model for internet-based intrusion detection systems.

Analysis of Thompson Sampling for the Multi-armed Bandit Problem

For the first time, it is shown that Thompson Sampling algorithm achieves logarithmic expected regret for the stochastic multi-armed bandit problem.

Quickest detection in censoring sensor networks

  • Y. Mei
  • Computer Science
    2011 IEEE International Symposium on Information Theory Proceedings
  • 2011
The quickest change detection problem is studied in a general context of monitoring a large number of data streams in sensor networks when the “trigger event” may affect different sensors

A Change-Detection-Based Thompson Sampling Framework for Non-Stationary Bandits

The results show that TS-CD not only outperforms the classical max-power RAT selection strategy but also other actively adaptive and passively adaptive bandit algorithms that are designed for non-stationary environments.

Optimal Detection of a Change in Distribution

A stopping rule that is a limit of Bayes rules is first derived and an almost minimax rule is presented; i.e. a stopping rule which satisfies E(N^\ast\mid\nu = \infty) = B.

On Optimum Methods in Quickest Detection Problems

In this paper optimum methods are developed for observing a process (1), in which the moment when a “disorder” $\theta$ appears is not known. The basic quantity characterizing the quality of this

Some aspects of the sequential design of experiments

Until recently, statistical theory has been restricted to the design and analysis of sampling experiments in which the size and composition of the samples are completely determined before the
...