human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "remote estimation of the wiener process over a channel with random delay"):
  Abstract: In this paper, we consider a problem of sampling a Wiener process, with samples forwarded to a remote estimator via a channel with queueing and random delay. The estimator reconstructs a real-time estimate of the signal from causally received samples. Motivated by recent research on Age-of-Information, we study the optimal sampling strategy for minimizing the mean square estimation error subject to a sampling-rate constraint. We prove that the optimal sampling strategy is a threshold policy, and find the optimal threshold. This threshold is determined by the sampling-rate constraint and how much the Wiener process varies during the channel delay. An unexpected consequence is that even in the absence of the sampling-rate constraint, the optimal strategy is not zero-wait sampling in which a new sample is taken once the previous sample is delivered; rather, there is a non-zero waiting time before taking the next sample. Further, if the sampling times are independent of the observed Wiener process, the optimal sampling problem reduces to an age-of-information optimization problem that has been recently solved. Our comparisons show that the estimation error of the optimal sampling policy is much smaller than those of age-optimal sampling, zero-wait sampling, and classic uniform sampling.

Includes members:
  Member "scheduling status updates to minimize age of information with an energy harvesting sensor":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "urgency of information for context aware timely status updates in remote control systems")
  Member "age optimal information updates in multihop networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "timely updates by multiple sources the m m 1 queue revisited")
  Member "update or wait how to keep your data fresh":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "who should google scholar update more often")
  Member "optimizing data freshness throughput and delay in multi server information update systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "who should google scholar update more often")
  Member "on remote estimation with multiple communication channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "optimal policies for status update generation in a wireless system with heterogeneous traffic")
  Member "optimal estimation with limited measurements and noisy communication":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "optimal causal rate constrained sampling of the wiener process")
  Member "distortion transmission trade off in real time transmission of markov sources":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "infinite horizon optimal transmission power control for remote state estimation over fading channels")
  Member "optimal strategies for communication and remote estimation with an energy harvesting sensor":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "optimal causal rate constrained sampling for a class of continuous markov processes")

Question: Please tell me which class the source paper 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)