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: "an information inequality and evaluation of marton s inner bound for binary input broadcast channels"
  Abstract: We establish an information inequality that is intimately connected to the evaluation of the sum rate given by Marton's inner bound for two receiver broadcast channels with a binary input alphabet. This generalizes a recent result where the inequality was established for a particular channel, the binary skew-symmetric broadcast channel. The inequality implies that randomized time-division strategy indeed achieves the sum rate of Marton's inner bound for all binary input broadcast channels.

Connected through hyperedge HE-1 (induced by source paper "evaluation of marton s inner bound for the general broadcast channel"):
  with members:
    - "the capacity region of classes of product broadcast channels"
    - "an information inequality for the bssc channel"
    - "evaluation of marton s inner bound for the general broadcast channel"
    - "an outer bound for 2 receiver discrete memoryless broadcast channels"
    - "rate regions for relay broadcast channels"

Connected through hyperedge HE-2 (induced by source paper "on marton s inner bound for broadcast channels"):
  with members:
    - "evaluation of marton s inner bound for the general broadcast channel"
    - "an information inequality for the bssc channel"
    - "evaluation of marton s inner bound for the general broadcast channel"

Connected through hyperedge HE-3 (induced by source paper "on broadcast channels with binary inputs and symmetric outputs"):
  with members:
    - "capacity regions of two new classes of 2 receiver broadcast channels"

Connected through hyperedge HE-4 (induced by source paper "evaluation of marton s inner bound for the general broadcast channel"):
  with members:
    - "evaluation of marton s inner bound for the general broadcast channel"
    - "the capacity region of classes of product broadcast channels"
    - "an information inequality for the bssc channel"
    - "an outer bound for 2 receiver discrete memoryless broadcast channels"
    - "rate regions for relay broadcast channels"

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)