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: "decentralized sequential change detection using physical layer fusion"
  Abstract: The problem of decentralized sequential detection with conditionally independent observations is studied. The sensors form a star topology with a central node called fusion center as the hub. The sensors make noisy observations of a parameter that changes from an initial state to a final state at a random time where the random change time has a geometric distribution. The sensors amplify and forward the observations over a wireless Gaussian multiple access channel and operate under either a power constraint or an energy constraint. The optimal transmission strategy at each stage is shown to be the one that maximizes a certain Ali-Silvey distance between the distributions for the hypotheses before and after the change. Simulations demonstrate that the proposed analog technique has lower detection delays when compared with existing schemes. Simulations further demonstrate that the energy-constrained formulation enables better use of the total available energy than the power-constrained formulation in the change detection problem.

Connected through hyperedge HE-1 (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"
    - "one shot schemes for decentralized quickest change detection"

Connected through hyperedge HE-2 (induced by source paper "quickest change detection in adaptive censoring sensor networks"):
  with members:
    - "quickest change detection with a censoring sensor in the minimax setting"
    - "bayesian quickest change point detection with sampling right constraints"
    - "non bayesian quickest change detection with stochastic sample right constraints"

Connected through hyperedge HE-3 (induced by source paper "optimum sleep wake scheduling of sensors for quickest event detection in small extent wireless sensor networks"):
  with members:
    - "delay optimal event detection on ad hoc wireless sensor networks"

Connected through hyperedge HE-4 (induced by source paper "generalized analysis of a distributed energy efficient algorithm for change detection"):
  with members:
    - "an efficient algorithm for cooperative spectrum sensing in cognitive radio networks"

Connected through hyperedge HE-5 (induced by source paper "separable convex optimization problems with linear ascending constraints"):
  with members:
    - "approximately universal codes over slow fading channels"

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)