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: "age of information with finite horizon and partial updates"
  Abstract: A resource-constrained system monitors a source of information by requesting a finite number of updates subject to random transmission delays. An a priori fixed update request policy is shown to minimize a polynomial penalty function of the age of information over arbitrary time horizons. Partial updates, compressed updates with reduced transmission and information content, in the presented model are shown to incur an age penalty independent of the compression. Finite horizons are shown to have better performance in terms of second order statistic relative to infinite horizons.

Connected through hyperedge HE-1 (induced by source paper "who should google scholar update more often"):
  with members:
    - "optimal selective encoding for timely updates"
    - "trading off computation with transmission in status update systems"
    - "average peak age of information minimization in uav assisted iot networks"
    - "a reinforcement learning framework for optimizing age of information in rf powered communication systems"
    - "age of information aware cache updating with file and age dependent update durations"
    - "reducing age of information for computation intensive messages via packet replacement"
    - "timely distributed computation with stragglers"
    - "age of information in multicast networks with multiple update streams"

Connected through hyperedge HE-2 (induced by source paper "partial updates losing information for freshness"):
  with members:
    - "optimal selective encoding for timely updates"
    - "trading off computation with transmission in status update systems"
    - "on timely channel coding with hybrid arq"
    - "reducing age of information for computation intensive messages via packet replacement"
    - "timely distributed computation with stragglers"
    - "age of information in multicast networks with multiple update streams"
    - "age of information for updates with distortion"
    - "using erasure feedback for online timely updating with an energy harvesting sensor"

Connected through hyperedge HE-3 (induced by source paper "optimal selective encoding for timely updates"):
  with members:
    - "trading off computation with transmission in status update systems"
    - "on timely channel coding with hybrid arq"
    - "reducing age of information for computation intensive messages via packet replacement"
    - "timely distributed computation with stragglers"
    - "age of information in multicast networks with multiple update streams"
    - "age of information in g g 1 1 systems age expressions bounds special cases and optimization"
    - "age of information for updates with distortion"
    - "using erasure feedback for online timely updating with an energy harvesting sensor"

Connected through hyperedge HE-4 (induced by source paper "age of information for updates with distortion constant and age dependent distortion constraints"):
  with members:
    - "age of information for computation intensive messages in mobile edge computing"
    - "age of information aware cache updating with file and age dependent update durations"
    - "timely distributed computation with stragglers"
    - "age of information for updates with distortion"
    - "towards the tradeoff between service performance and information freshness"
    - "online timely status updates with erasures for energy harvesting sensors"
    - "minimizing age of information with soft updates"
    - "optimal status updating for an energy harvesting sensor with a noisy channel"

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)