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 strong direct product theorem in terms of the smooth rectangle bound"
  Abstract: A strong direct product theorem states that, in order to solve k instances of a problem, if we provide less than k times the resource required to compute one instance, then the probability of overall success is exponentially small in k. In this paper, we consider the model of two-way public-coin communication complexity and show a strong direct product theorem for all relations in terms of the smooth rectangle bound, introduced by Jain and Klauck as a generic lower bound method in this model. Our result therefore uniformly implies a strong direct product theorem for all relations for which an (asymptotically) optimal lower bound can be provided using the smooth rectangle bound, for example Inner Product, Greater-Than, Set-Disjointness, Gap-Hamming Distance etc. Our result also implies near optimal direct product results for several important functions and relations used to show exponential separations between classical and quantum communication complexity, for which near optimal lower bounds are provided using the rectangle bound, for example by Raz [1999], Gavinsky [2008] and Klartag and Regev [2011]. In fact we are not aware of any relation for which it is known that the smooth rectangle bound does not provide an optimal lower bound. This lower bound subsumes many of the other lower bound methods, for example the rectangle bound (a.k.a the corruption bound), the smooth discrepancy bound (a.k.a the \gamma_2 bound) which in turn subsumes the discrepancy bound, the subdistribution bound and the conditional min-entropy bound. #R##N#We show our result using information theoretic arguments. A key tool we use is a sampling protocol due to Braverman [2012], in fact a modification of it used by Kerenidis, Laplante, Lerays, Roland and Xiao [2012].

Connected through hyperedge HE-1 (induced by source paper "simulation theorems via pseudorandom properties"):
  with members:
    - "lower bounds on information complexity via zero communication protocols and applications"
    - "information equals amortized communication"
    - "improved direct product theorems for randomized query complexity"
    - "strong direct product theorems for quantum communication and query complexity"
    - "a direct sum theorem in communication complexity via message compression"

Connected through hyperedge HE-2 (induced by source paper "information complexity and the quest for interactive compression a survey"):
  with members:
    - "lower bounds on information complexity via zero communication protocols and applications"
    - "information equals amortized communication"
    - "a discrepancy lower bound for information complexity"
    - "strong direct product theorems for quantum communication and query complexity"
    - "a strong direct product theorem for disjointness"

Connected through hyperedge HE-3 (induced by source paper "relaxed partition bound is quadratically tight for product distributions"):
  with members:
    - "lower bounds on information complexity via zero communication protocols and applications"
    - "the partition bound for classical communication complexity and query complexity"

Connected through hyperedge HE-4 (induced by source paper "a strong direct product theorem for the tribes function via the smooth rectangle bound"):
  with members:
    - "a direct product theorem for bounded round public coin randomized communication complexity"
    - "lower bounds on information complexity via zero communication protocols and applications"
    - "an optimal lower bound on the communication complexity of gap hamming distance"
    - "the partition bound for classical communication complexity and query complexity"
    - "a strong direct product theorem for disjointness"

Connected through hyperedge HE-5 (induced by source paper "lower bounds on information complexity via zero communication protocols and applications"):
  with members:
    - "information complexity versus corruption and applications to orthogonality and gap hamming"
    - "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"

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)