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: "a generalized typicality for abstract alphabets"
  Abstract: A new notion of typicality for arbitrary probability measures on standard Borel spaces is proposed, which encompasses the classical notions of weak and strong typicality as special cases. Useful lemmas about strong typical sets, including conditional typicality lemma, joint typicality lemma, and packing and covering lemmas, which are fundamental tools for deriving many inner bounds of various multi-terminal coding problems, are obtained in terms of the proposed notion. This enables us to directly generalize lots of results on finite alphabet problems to general problems involving abstract alphabets, without any complicated additional arguments. For instance, quantization procedure is no longer necessary to achieve such generalizations. Another fundamental lemma, Markov lemma, is also obtained but its scope of application is quite limited compared to others. Yet, an alternative theory of typical sets for Gaussian measures, free from this limitation, is also developed. Some remarks on a possibility to generalize the proposed notion for sources with memory are also given.

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 "on exact and infty r enyi common informations"):
  with members:
    - "corrections to wyner s common information under r enyi divergence measures"
    - "exact channel synthesis"
    - "strong functional representation lemma and applications to coding theorems"
    - "distributed simulation of continuous random variables"
    - "generalized common information common information extraction and private sources synthesis"
    - "exact common information"
    - "renyi divergence and kullback leibler divergence"
    - "wyner s common information generalizations and a new lossy source coding interpretation"

Connected through hyperedge HE-3 (induced by source paper "the likelihood encoder for lossy compression"):
  with members:
    - "joint source channel secrecy using hybrid coding"
    - "a rate distortion based secrecy system with side information at the decoders"
    - "the likelihood encoder for lossy source compression"
    - "a technique for deriving one shot achievability results in network information theory"
    - "non asymptotic output statistics of random binning and its applications"
    - "a connection between good rate distortion codes and backward dmcs"
    - "the likelihood encoder for source coding"
    - "distributed channel synthesis"

Connected through hyperedge HE-4 (induced by source paper "rate distortion for lossy in network function computation information dissipation and sequential reverse water filling"):
  with members:
    - "wasserstein continuity of entropy and outer bounds for interference channels"
    - "computing linear transformations with unreliable components"
    - "a generalized cut set bound for deterministic multi flow networks and its applications"
    - "dissipation of information in channels with input constraints"
    - "strong data processing inequalities and phi sobolev inequalities for discrete channels"
    - "on cooperation in multi terminal computation and rate distortion"
    - "network coding for computing cut set bounds"
    - "optimal function computation in directed and undirected graphs"

Connected through hyperedge HE-5 (induced by source paper "scalable capacity bounding models for wireless networks"):
  with members:
    - "the likelihood encoder for lossy compression"
    - "distributed channel synthesis"
    - "capacity of multiple unicast in wireless networks a polymatroidal approach"
    - "wireless network information flow a deterministic approach"
    - "separation of source network coding and channel coding in wireline networks"
    - "path gain algebraic formulation for the scalar linear network coding problem"
    - "optimality and approximate optimality of source channel separation in networks"
    - "a theory of network equivalence parts i and ii"

Connected through hyperedge HE-6 (induced by source paper "the likelihood encoder for lossy source compression"):
  with members:
    - "the likelihood encoder for source coding"
    - "distributed channel synthesis"
    - "rate distortion theory for secrecy systems"
    - "hybrid coding an interface for joint source channel coding and network communication"

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)