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: "one shot schemes for decentralized quickest change detection"
  Abstract: This work considers the problem of quickest detection with N distributed sensors that receive continuous sequential observations from the environment. These sensors employ cumulative sum (CUSUM) strategies and communicate to a central fusion center by one shot schemes. One shot schemes are schemes in which the sensors communicate with the fusion center only once, after which they must signal a detection. The communication is clearly asynchronous and the case is considered in which the fusion center employs a minimal strategy, which means that it declares an alarm when the first communication takes place. It is assumed that the observations received at the sensors are independent and that the time points at which the appearance of a signal can take place are different. It is shown that there is no loss of performance of one shot schemes as compared to the centralized case in an extended Lorden min-max sense, since the minimum of N CUSUMs is asymptotically optimal as the mean time between false alarms increases without bound.

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"
    - "quickest change detection of a markov process across a sensor array"

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"
    - "quickest change detection of a markov process across a sensor array"

Connected through hyperedge HE-3 (induced by source paper "distributed bayesian quickest change detection in sensor networks via two layer large deviation analysis"):
  with members:
    - "distributed kalman filtering over massive data sets analysis through large deviations of random riccati equations"
    - "distributed detection over noisy networks large deviations analysis"
    - "decentralized sequential change detection using physical layer fusion"

Connected through hyperedge HE-4 (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"
    - "quickest change detection of a markov process across a sensor array"

Connected through hyperedge HE-5 (induced by source paper "quickest change point detection and identification across a generic sensor array"):
  with members:
    - "quickest change detection of a markov process across a sensor array"

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)