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: "refinement of the sphere packing bound asymmetric channels"
  Abstract: We provide a refinement of the sphere-packing bound for constant composition codes over asymmetric discrete memoryless channels that improves the pre-factor in front of the exponential term. The order of our pre-factor is $\Omega(N^{-1/2(1+\epsilon + \rho_{R}^{\ast})})$ for any $\epsilon >0$, where $\rho_{R}^{\ast}$ is the maximum absolute-value subdifferential of the sphere-packing exponent at rate $R$ and $N$ is the blocklength.

Connected through hyperedge HE-1 (induced by source paper "refined strong converse for the constant composition codes"):
  with members:
    - "on exact asymptotics of the error probability in channel coding symmetric channels"
    - "a simple derivation of the refined spb for the constant composition codes"
    - "the augustin capacity and center"
    - "the sphere packing bound via augustin s method"
    - "renyi divergence and kullback leibler divergence"

Connected through hyperedge HE-2 (induced by source paper "second order asymptotics of sequential hypothesis testing"):
  with members:
    - "reliability of sequential hypothesis testing can be achieved by an almost fixed length test"
    - "asymptotic estimates in information theory with non vanishing error probabilities"
    - "refinement of the random coding bound"
    - "second order asymptotics in fixed length source coding and intrinsic randomness"

Connected through hyperedge HE-3 (induced by source paper "a simple derivation of the refined sphere packing bound under certain symmetry hypotheses"):
  with members:
    - "on exact asymptotics of the error probability in channel coding symmetric channels"
    - "a simple derivation of the refined spb for the constant composition codes"
    - "error probability bounds for gaussian channels under maximal and average power constraints"
    - "the renyi capacity and center"
    - "saddlepoint approximations for short packet wireless communications"
    - "the sphere packing bound for memoryless channels"
    - "the sphere packing bound for dspcs with feedback a la augustin"
    - "the augustin capacity and center"

Connected through hyperedge HE-4 (induced by source paper "on exact asymptotics of the error probability in channel coding symmetric channels"):
  with members:
    - "a new method for employing feedback to improve coding performance"
    - "the sphere packing bound for dspcs with feedback a la augustin"
    - "exact asymptotics for the random coding error probability"
    - "the saddlepoint approximation unified random coding asymptotics for fixed and varying rates"
    - "a tight upper bound for the third order asymptotics for most discrete memoryless channels"
    - "mismatched decoding error exponents second order rates and saddlepoint approximations"
    - "refinement of the random coding bound"
    - "a derivation of the asymptotic random coding prefactor"

Connected through hyperedge HE-5 (induced by source paper "a simple derivation of the refined spb for the constant composition codes"):
  with members:
    - "the sphere packing bound for memoryless channels"
    - "the augustin capacity and center"
    - "the sphere packing bound via augustin s method"
    - "constant compositions in the sphere packing bound for classical quantum channels"
    - "renyi divergence and kullback leibler divergence"
    - "lower bounds on the probability of error for classical and classical quantum channels"

Connected through hyperedge HE-6 (induced by source paper "the sphere packing bound for memoryless channels"):
  with members:
    - "on exact asymptotics of the error probability in channel coding symmetric channels"
    - "a simple derivation of the refined spb for the constant composition codes"
    - "the renyi capacity and center"
    - "saddlepoint approximations for short packet wireless communications"
    - "the augustin capacity and center"
    - "the augustin center and the sphere packing bound for memoryless channels"
    - "the capacity of gaussian mimo channels under total and per antenna power constraints"
    - "the sphere packing bound via augustin s method"

Connected through hyperedge HE-7 (induced by source paper "the error probability of generalized perfect codes via the meta converse"):
  with members:
    - "weak flip codes and their optimality on the binary erasure channel"
    - "lossy joint source channel coding in the finite blocklength regime"

Connected through hyperedge HE-8 (induced by source paper "discrete lossy gray wyner revisited second order asymptotics large and moderate deviations"):
  with members:
    - "second order region for gray wyner network"
    - "strong successive refinability and rate distortion complexity tradeoff"
    - "asymptotic estimates in information theory with non vanishing error probabilities"
    - "second order coding region for the discrete lossy gray wyner source coding problem"
    - "the lossy common information of correlated sources"
    - "second order coding rates for channels with state"
    - "a technique for deriving one shot achievability results in network information theory"
    - "refinement of the random coding bound"

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)