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: "optimal age over erasure channels"
  Abstract: Previous works on age of information and erasure channels have dealt with specific models and computed the average age or average peak age for certain settings. In this paper, given a source that produces a letter every $T_s$ seconds and an erasure channel that can be used every $T_c$ seconds, we ask what is the coding strategy that minimizes the time-average "age of information" that an observer of the channel output incurs. We will see that one has to distinguish the cases when the source and channel-input alphabets have equal or different size. In the first case, we show that a trivial coding strategy is optimal and a closed form expression for the age may be derived. In the second, we use random coding argument to bound the average age and show that the average age achieved using random codes converges to the optimal average age as the source alphabet becomes large.

Connected through hyperedge HE-1 (induced by source paper "benefits of coding on age of information in broadcast networks"):
  with members:
    - "sampling for remote estimation through queues age of information and beyond"
    - "scheduling policies for minimizing age of information in broadcast wireless networks"
    - "the age of information in networks moments distributions and sampling"
    - "online timely status updates with erasures for energy harvesting sensors"
    - "distributed scheduling algorithms for optimizing information freshness in wireless networks"
    - "age minimal online policies for energy harvesting sensors with random battery recharges"
    - "delay and peak age violation probability in short packet transmissions"
    - "optimizing age of information in wireless networks with perfect channel state information"

Connected through hyperedge HE-2 (induced by source paper "adaptive coding for information freshness in a two user broadcast erasure channel"):
  with members:
    - "benefits of coding on age of information in broadcast networks"
    - "age optimal transmission of rateless codes in an erasure channel"
    - "scheduling policies for minimizing age of information in broadcast wireless networks"
    - "coded status updates in an energy harvesting erasure channel"
    - "controlling packet drops to improve freshness of information"
    - "age of information minimization for an energy harvesting source with updating erasures with and without feedback"
    - "when to preempt age of information minimization under link capacity constraint"
    - "timely lossless source coding for randomly arriving symbols"

Connected through hyperedge HE-3 (induced by source paper "age of information in random access channels"):
  with members:
    - "benefits of coding on age of information in broadcast networks"
    - "minimizing the age of information in wireless networks with stochastic arrivals"
    - "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"
    - "timely status update in massive iot systems decentralized scheduling for wireless uplinks"
    - "distributed scheduling algorithms for optimizing information freshness in wireless networks"
    - "age of information performance of multiaccess strategies with packet management"
    - "solving fractional polynomial problems by polynomial optimization theory"

Connected through hyperedge HE-4 (induced by source paper "on timely channel coding with hybrid arq"):
  with members:
    - "age optimal transmission of rateless codes in an erasure channel"
    - "coded status updates in an energy harvesting erasure channel"
    - "joint status sampling and updating for minimizing age of information in the internet of things"
    - "optimizing information freshness in wireless networks under general interference constraints"
    - "delay and peak age violation probability in short packet transmissions"
    - "age minimal transmission for energy harvesting sensors with finite batteries online policies"
    - "optimal status update for age of information minimization with an energy harvesting source"
    - "average age of information with hybrid arq under a resource constraint"

Connected through hyperedge HE-5 (induced by source paper "on the age of information in erasure channels with feedback"):
  with members:
    - "a reinforcement learning framework for optimizing age of information in rf powered communication systems"
    - "age of information in multiple sensing of a single source"
    - "benefits of coding on age of information in broadcast networks"
    - "adaptive coding for information freshness in a two user broadcast erasure channel"
    - "timely updates over an erasure channel"
    - "status updates through m g 1 1 queues with harq"
    - "the age of information real time status updating by multiple sources"
    - "on the age of information in status update systems with packet management"

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)