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 the error exponents of arq channels with deadlines"
  Abstract: In this correspondence, we consider communication over automatic repeat request (ARQ) memoryless channels with deadlines. In particular, an upper bound L is imposed on the maximum number of ARQ transmission rounds. In this setup, it is shown that incremental redundancy ARQ outperforms Forney's memoryless decoding in terms of the achievable error exponents.

Connected through hyperedge HE-1 (induced by source paper "errors and erasures decoding for block codes with feedback"):
  with members:
    - "variations on a theme by schalkwijk and kailath"
    - "achievable error exponents for channel with side information erasure and list decoding"
    - "error exponents for the gaussian channel with active noisy feedback"
    - "a simple converse of burnashev s reliability function"
    - "a neyman pearson approach to universal erasure and list decoding"
    - "error exponents for variable length block codes with feedback and cost constraints"
    - "error exponents of erasure list decoding revisited via moments of distance enumerators"

Connected through hyperedge HE-2 (induced by source paper "error exponents of erasure list decoding revisited via moments of distance enumerators"):
  with members:
    - "error exponents of optimum decoding for the interference channel"
    - "relations between random coding exponents and the statistical physics of random codes"

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)