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: "on remote estimation with multiple communication channels"
  Abstract: This paper considers a sequential sensor scheduling and remote estimation problem with multiple communication channels. Departing from the classical remote estimation paradigm, which involves one communication channel (noiseless or noisy), we consider here the more realistic setting of two channels with different characteristics (one is cheap but noisy, the other one is costly but noiseless). We first show, via a counter-example, that the common folklore of applying symmetric threshold-based policy, which is well known to be optimal (for unimodal state densities) in the classical remote estimation problem, can no longer be optimal in our setting. In view of that, and in order to make the problem tractable, we introduce a side channel which signals to the receiver the sign of the underlying state. We show, under some technical assumptions, that a threshold-in-threshold based communication scheduling is optimal. The impact of the results is analyzed numerically based on dynamic programming. This numerical analysis reveals some rather surprising results inheriting known properties from the single channel settings, such as not exhausting all the opportunities available for the noisy channel.

Connected through hyperedge HE-1 (induced by source paper "optimal policies for status update generation in a wireless system with heterogeneous traffic"):
  with members:
    - "optimizing age of information in wireless networks with perfect channel state information"
    - "content based status updates"
    - "scheduling policies for age minimization in wireless networks with unknown channel state"
    - "average age of information with hybrid arq under a resource constraint"
    - "age optimal information updates in multihop networks"
    - "age and value of information non linear age case"
    - "remote estimation of the wiener process over a channel with random delay"
    - "update or wait how to keep your data fresh"

Connected through hyperedge HE-2 (induced by source paper "remote estimation over a packet drop channel with markovian state"):
  with members:
    - "infinite horizon optimal transmission power control for remote state estimation over fading channels"
    - "decentralized stochastic control with partial history sharing a common information approach"
    - "optimal strategies for communication and remote estimation with an energy harvesting sensor"

Connected through hyperedge HE-3 (induced by source paper "sampling of the wiener process for remote estimation over a channel with random delay"):
  with members:
    - "the dispersion of the gauss markov source"
    - "remote estimation over a packet drop channel with markovian state"
    - "scheduling status updates to minimize age of information with an energy harvesting sensor"
    - "age optimal information updates in multihop networks"
    - "remote estimation of the wiener process over a channel with random delay"
    - "the distortion rate function of sampled wiener processes"
    - "update or wait how to keep your data fresh"
    - "optimizing data freshness throughput and delay in multi server information update systems"

Connected through hyperedge HE-4 (induced by source paper "remote estimation of the wiener process over a channel with random delay"):
  with members:
    - "scheduling status updates to minimize age of information with an energy harvesting sensor"
    - "age optimal information updates in multihop networks"
    - "update or wait how to keep your data fresh"
    - "optimizing data freshness throughput and delay in multi server information update systems"
    - "optimal estimation with limited measurements and noisy communication"
    - "distortion transmission trade off in real time transmission of markov sources"
    - "optimal strategies for communication and remote estimation with an energy harvesting sensor"
    - "paging and registration in cellular networks jointly optimal policies and an iterative algorithm"

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)