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: "information complexity versus corruption and applications to orthogonality and gap hamming"
  Abstract: Three decades of research in communication complexity have led to the invention of a number of techniques to lower bound randomized communication complexity. The majority of these techniques involve properties of large submatrices (rectangles) of the truth-table matrix defining a communication problem. The only technique that does not quite fit is information complexity, which has been investigated over the last decade. Here, we connect information complexity to one of the most powerful "rectangular" techniques: the recently-introduced smooth corruption (or "smooth rectangle") bound. We show that the former subsumes the latter under rectangular input distributions. We conjecture that this subsumption holds more generally, under arbitrary distributions, which would resolve the long-standing direct sum question for randomized communication. As an application, we obtain an optimal $\Omega(n)$ lower bound on the information complexity---under the {\em uniform distribution}---of the so-called orthogonality problem (ORT), which is in turn closely related to the much-studied Gap-Hamming-Distance (GHD). The proof of this bound is along the lines of recent communication lower bounds for GHD, but we encounter a surprising amount of additional technical detail.

Connected through hyperedge HE-1 (induced by source paper "r enyi information complexity and an information theoretic characterization of the partition bound"):
  with members:
    - "tension bounds for information complexity"
    - "lower bounds on information complexity via zero communication protocols and applications"
    - "information equals amortized communication"
    - "a discrepancy lower bound for information complexity"
    - "the partition bound for classical communication complexity and query complexity"
    - "a direct sum theorem in communication complexity via message compression"

Connected through hyperedge HE-2 (induced by source paper "tension bounds for information complexity"):
  with members:
    - "assisted common information with an application to secure two party sampling"
    - "on the communication complexity of secure computation"
    - "lower bounds on information complexity via zero communication protocols and applications"
    - "information equals amortized communication"
    - "a discrepancy lower bound for information complexity"
    - "a direct sum theorem in communication complexity via message compression"

Connected through hyperedge HE-3 (induced by source paper "lower bounds on information complexity via zero communication protocols and applications"):
  with members:
    - "a strong direct product theorem in terms of the smooth rectangle bound"
    - "information equals amortized communication"
    - "a discrepancy lower bound for information complexity"
    - "tight bounds for distributed functional monitoring"
    - "an optimal lower bound on the communication complexity of gap hamming distance"
    - "the space complexity of recognizing well parenthesized expressions in the streaming model the index function revisited"
    - "quantum one way communication is exponentially stronger than classical communication"
    - "the partition bound for classical communication complexity and query complexity"

Connected through hyperedge HE-4 (induced by source paper "superlinear lower bounds for multipass graph processing"):
  with members:
    - "better bounds for matchings in the streaming model"
    - "a direct product theorem for bounded round public coin randomized communication complexity"
    - "lower bounds on information complexity via zero communication protocols and applications"
    - "maximum matching in semi streaming with few passes"
    - "information equals amortized communication"
    - "a discrepancy lower bound for information complexity"
    - "improved approximation guarantees for weighted matching in the semi streaming model"
    - "linear programming in the semi streaming model with application to the maximum matching problem"

Connected through hyperedge HE-5 (induced by source paper "tight bounds for distributed functional monitoring"):
  with members:
    - "optimal random sampling from distributed streams revisited"
    - "a lower bound for estimating high moments of a data stream"
    - "randomized algorithms for tracking distributed count frequencies and ranks"
    - "lower bounds for number in hand multiparty communication complexity made easy"
    - "polynomial estimators for high frequency moments"
    - "information cost tradeoffs for augmented index and streaming language recognition"
    - "fast moment estimation in data streams in optimal space"
    - "an optimal lower bound on the communication complexity of gap hamming distance"

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.CC(Computational Complexity)