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 listsize capacity with feedback"
  Abstract: The listsize capacity of a discrete memoryless channel is the largest transmission rate for which the expectation---or, more generally, the $\rho$-th moment---of the number of messages that could have produced the output of the channel approaches one as the blocklength tends to infinity. We show that for channels with feedback this rate is upper-bounded by the maximum of Gallager's $E_0$ function divided by $\rho$, and that equality holds when the zero-error capacity of the channel is positive. To establish this inequality we prove that feedback does not increase the cutoff rate. Relationships to other notions of channel capacity are explored.

Connected through hyperedge HE-1 (induced by source paper "the renyi capacity and center"):
  with members:
    - "a strong converse bound for multiple hypothesis testing with applications to high dimensional estimation"
    - "the sphere packing bound for memoryless channels"
    - "operational interpretation of renyi information measures via composite hypothesis testing against product and markov distributions"
    - "the sphere packing bound for dspcs with feedback a la augustin"
    - "the augustin capacity and center"
    - "the augustin center and the sphere packing bound for memoryless channels"
    - "analysis of remaining uncertainties and exponents under various conditional r e nyi entropies"
    - "on renyi entropy power inequalities"

Connected through hyperedge HE-2 (induced by source paper "guessing attacks on distributed storage systems"):
  with members:
    - "distributed task encoding"
    - "distributed storage for data security"
    - "encoding tasks and renyi entropy"
    - "guesswork large deviations and shannon entropy"
    - "the shannon cipher system with a guessing wiretapper general sources"
    - "guessing revisited a large deviations approach"
    - "mds codes on the erasure erasure wiretap channel"
    - "guessing under source uncertainty"

Connected through hyperedge HE-3 (induced by source paper "arimoto r enyi conditional entropy and bayesian m ary hypothesis testing"):
  with members:
    - "guessing attacks on distributed storage systems"
    - "f divergence inequalities"
    - "list decoding random coding exponents and expurgated exponents"
    - "encoding tasks and renyi entropy"
    - "renyi divergence and kullback leibler divergence"
    - "moderate deviations analysis of binary hypothesis testing"
    - "on multiple hypothesis testing with rejection option"
    - "guessing under source uncertainty"

Connected through hyperedge HE-4 (induced by source paper "reducing guesswork via an unreliable oracle"):
  with members:
    - "improved bounds on lossless source coding and guessing moments via r e nyi measures"
    - "investigating the distribution of password choices"
    - "guessing revisited a large deviations approach"
    - "optimal feedback communication via posterior matching"
    - "guessing under source uncertainty"

Connected through hyperedge HE-5 (induced by source paper "the zero undetected error capacity approaches the sperner capacity"):
  with members:
    - "errors and erasures decoding for block codes with feedback"

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)