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: "error exponent for multiple access channels lower bounds"
  Abstract: A unified framework to obtain all known lower bounds (random coding, typical random coding and expurgated bound) on the reliability function of a point-to-point discrete memoryless channel (DMC) is presented. By using a similar idea for a two-user discrete memoryless (DM) multiple-access channel (MAC), three lower bounds on the reliability function are derived. The first one (random coding) is identical to the best known lower bound on the reliability function of DM-MAC. It is shown that the random coding bound is the performance of the average code in the constant composition code ensemble. The second bound (Typical random coding) is the typical performance of the constant composition code ensemble. To derive the third bound (expurgated), we eliminate some of the codewords from the codebook with larger rate. This is the first bound of this type that explicitly uses the method of expurgation for MACs. It is shown that the exponent of the typical random coding and the expurgated bounds are greater than or equal to the exponent of the known random coding bounds for all rate pairs. Moreover, an example is given where the exponent of the expurgated bound is strictly larger. All these bounds can be universally obtained for all discrete memoryless MACs with given input and output alphabets.

Connected through hyperedge HE-1 (induced by source paper "error exponents for asynchronous multiple access channels controlled asynchronism may outperform synchronism"):
  with members:
    - "error exponents of typical random trellis codes"
    - "shifted coded slotted aloha"
    - "distributed structure joint expurgation for the multiple access channel"
    - "universal random access error exponents for codebooks of different word lengths"
    - "random access and source channel coding error exponents for multiple access channels"

Connected through hyperedge HE-2 (induced by source paper "distributed structure joint expurgation for the multiple access channel"):
  with members:
    - "a new upper bound on the average error exponent for multiple access channels"
    - "lattice strategies for the dirty multiple access channel"
    - "lattices for distributed source coding jointly gaussian sources and reconstruction of a linear function"

Connected through hyperedge HE-3 (induced by source paper "mismatched decoding error exponents second order rates and saddlepoint approximations"):
  with members:
    - "expurgated random coding ensembles exponents refinements and connections"
    - "multiuser coding techniques for mismatched decoding"
    - "a general formula for the mismatch capacity"
    - "refinement of the random coding bound"
    - "a derivation of the asymptotic random coding prefactor"
    - "on achievable rates for channels with mismatched decoding"
    - "moderate deviations in channel coding"
    - "refinement of the sphere packing bound asymmetric channels"

Connected through hyperedge HE-4 (induced by source paper "random access and source channel coding error exponents for multiple access channels"):
  with members:
    - "a generalized channel coding theory for distributed communication"
    - "a derivation of the source channel error exponent using non identical product distributions"
    - "error performance of channel coding in random access communication"
    - "a new approach to random access reliable communication and reliable collision detection"
    - "the dispersion of joint source channel coding"
    - "unequal error protection an information theoretic perspective"

Connected through hyperedge HE-5 (induced by source paper "multiuser random coding techniques for mismatched decoding"):
  with members:
    - "on the reliability function of the discrete memoryless relay channel"
    - "a counter example to the mismatched decoding converse for binary input discrete memoryless channels"
    - "expurgated random coding ensembles exponents refinements and connections"
    - "mismatched decoding error exponents second order rates and saddlepoint approximations"

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)