human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "quickest change detection of a markov process across a sensor array"
  Abstract: Recent attention in quickest change detection in the multisensor setting has been on the case where the densities of the observations change at the same instant at all the sensors due to the disruption. In this work, a more general scenario is considered where the change propagates across the sensors, and its propagation can be modeled as a Markov process. A centralized, Bayesian version of this problem is considered, with a fusion center that has perfect information about the observations and a priori knowledge of the statistics of the change process. The problem of minimizing the average detection delay subject to false alarm constraints is formulated in a dynamic programming framework. Insights into the structure of the optimal stopping rule are presented. In the limiting case of rare disruptions, it is shown that the structure of the optimal test reduces to thresholding the a posteriori probability of the hypothesis that no change has happened. Under a certain condition on the Kullback-Leibler (K-L) divergence between the post- and the pre-change densities, it is established that the threshold test is asymptotically optimal (in the vanishing false alarm probability regime). It is shown via numerical studies that this low-complexity threshold test results in a substantial improvement in performance over naive tests such as a single-sensor test or a test that incorrectly assumes that the change propagates instantaneously.

Connected through hyperedge HE-1 (induced by source paper "multisensor sequential change detection with unknown change propagation pattern"):
  with members:
    - "real time detection of hybrid and stealthy cyber attacks in smart grid"
    - "distributed detection of a non cooperative target via generalized locally optimum approaches"
    - "cooperative change detection for voltage quality monitoring in smart grids"
    - "one shot schemes for decentralized quickest change detection"

Connected through hyperedge HE-2 (induced by source paper "consensus based distributed quickest detection of attacks with unknown parameters"):
  with members:
    - "attack detection in sensor network target localization systems with quantized data"
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "uplink performance of wideband massive mimo with one bit adcs"
    - "capacity analysis of one bit quantized mimo systems with transmitter channel state information"
    - "gossip algorithms for distributed signal processing"
    - "one shot schemes for decentralized quickest change detection"

Connected through hyperedge HE-3 (induced by source paper "active hypothesis testing for quickest anomaly detection"):
  with members:
    - "optimal index policies for anomaly localization in resource constrained cyber systems"
    - "universal outlier hypothesis testing"
    - "active sequential hypothesis testing"
    - "sequentiality and adaptivity gains in active hypothesis testing"
    - "controlled sensing for multihypothesis testing"
    - "one shot schemes for decentralized quickest change detection"

Connected through hyperedge HE-4 (induced by source paper "quickest change point detection and identification across a generic sensor array"):
  with members:
    - "one shot schemes for decentralized quickest change detection"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.IT(Information Theory)