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: "status from a random field how densely should one update"
  Abstract: In many applications, status information of a general spatial process, in contrast to a point information source, is of interest. In this paper, we consider a system where status information is drawn from a random field and transmitted to a fusion center through a wireless multiaccess channel. The optimal density of spatial sampling points to minimize the remote status estimation error is investigated. Assuming a one-dimensional Gauss Markov random field and an exponential correlation function, closed-form expressions of remote estimation error are obtained for First-Come First-Served (FCFS) and Last-Come First-Served (LCFS) service disciplines. The optimal spatial sampling density for the LCFS case is given explicitly. Simulation results are presented which agree with our analysis.

Connected through hyperedge HE-1 (induced by source paper "on the age of information in internet of things systems with correlated devices"):
  with members:
    - "age of information analysis for dynamic spectrum sharing"
    - "minimizing the age of information of cognitive radio based iot systems under a collision constraint"
    - "sampling for remote estimation through queues age of information and beyond"
    - "a reinforcement learning framework for optimizing age of information in rf powered communication systems"
    - "age of information in multiple sensing of a single source"
    - "age of information in multiple sensing"
    - "minimizing the age of information in a csma environment"
    - "scheduling to minimize age of information in multi state time varying networks with power constraints"

Connected through hyperedge HE-2 (induced by source paper "revealing much while saying less predictive wireless for status update"):
  with members:
    - "age of information vs value of information scheduling for cellular networked control systems"
    - "sampling for remote estimation through queues age of information and beyond"
    - "ai assisted low information latency wireless networking"
    - "closed form whittle s index enabled random access for timely status update"
    - "minimizing the age of information in a csma environment"
    - "scheduling policies for minimizing age of information in broadcast wireless networks"
    - "can decentralized status update achieve universally near optimal age of information in wireless multiaccess channels"
    - "distributed scheduling algorithms for optimizing information freshness in wireless networks"

Connected through hyperedge HE-3 (induced by source paper "minimizing the age of information from sensors with common observations"):
  with members:
    - "scheduling policies for age minimization in wireless networks with unknown channel state"
    - "status updates over unreliable multiaccess channels"
    - "five disruptive technology directions for 5g"
    - "a contextual bandit approach to personalized news article recommendation"

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)