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: "opportunistic capacity and error exponent regions for compound channel with feedback"
  Abstract: Variable length communication over a compound channel with feedback is considered. Traditionally, capacity of a compound channel without feedback is defined as the maximum rate that is determined before the start of communication such that communication is reliable. This traditional definition is pessimistic. In the presence of feedback, an opportunistic definition is given. Capacity is defined as the maximum rate that is determined at the end of communication such that communication is reliable. Thus, the transmission rate can adapt to the channel chosen by nature. Under this definition, feedback communication over a compound channel is conceptually similar to multi-terminal communication. Transmission rate is a vector rather than a scalar; channel capacity is a region rather than a scalar; error exponent is a region rather than a scalar. In this paper, variable length communication over a compound channel with feedback is formulated, its opportunistic capacity region is characterized, and lower bounds for its error exponent region are provided..

Connected through hyperedge HE-1 (induced by source paper "on the reliability function of the common message broadcast channel with variable length feedback"):
  with members:
    - "common message broadcast channels with feedback in the nonasymptotic regime full feedback"
    - "on awgn channels and gaussian macs with variable length feedback"
    - "on gaussian macs with variable length feedback and non vanishing error probabilities"
    - "variable length coding with stop feedback for the common message broadcast channel in the nonasymptotic regime"
    - "on gaussian channels with feedback under expected power constraints and with non vanishing error probabilities"
    - "on using feedback in a gaussian channel"
    - "broadcasting a common message with variable length stop feedback codes"
    - "error exponents for the gaussian channel with active noisy feedback"

Connected through hyperedge HE-2 (induced by source paper "moderate deviation asymptotics for variable length codes with feedback"):
  with members:
    - "streaming data transmission in the moderate deviations and central limit regimes"
    - "extrinsic jensen shannon divergence applications to variable length coding"
    - "asymmetric evaluations of erasure and undetected error probabilities"
    - "moderate deviations in channel coding"
    - "moderate deviations of lossy source coding for discrete and gaussian sources"
    - "optimal feedback communication via posterior matching"
    - "a simple converse of burnashev s reliability function"
    - "error exponents for variable length block codes with feedback and cost constraints"

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)