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 quadratically tight partition bound for classical communication complexity and query complexity"
  Abstract: In this work we introduce, both for classical communication complexity and query complexity, a modification of the 'partition bound' introduced by Jain and Klauck [2010]. We call it the 'public-coin partition bound'. We show that (the logarithm to the base two of) its communication complexity and query complexity versions form, for all relations, a quadratically tight lower bound on the public-coin randomized communication complexity and randomized query complexity respectively.

Connected through hyperedge HE-1 (induced by source paper "randomized query complexity of sabotaged and composed functions"):
  with members:
    - "nearly optimal separations between communication or query complexity and partitions"
    - "composition limits and separating examples for some boolean function complexity measures"
    - "a composition theorem for decision tree complexity"
    - "improved direct product theorems for randomized query complexity"
    - "optimal direct sum results for deterministic and randomized decision tree complexity"
    - "the partition bound for classical communication complexity and query complexity"

Connected through hyperedge HE-2 (induced by source paper "nearly optimal separations between communication or query complexity and partitions"):
  with members:
    - "separating decision tree complexity from subcube partition complexity"
    - "composition limits and separating examples for some boolean function complexity measures"
    - "a composition theorem for decision tree complexity"
    - "the partition bound for classical communication complexity and query complexity"

Connected through hyperedge HE-3 (induced by source paper "almost quadratic gap between partition complexity and query communication complexity"):
  with members:
    - "separating decision tree complexity from subcube partition complexity"
    - "composition limits and separating examples for some boolean function complexity measures"
    - "the partition bound for classical communication complexity and query complexity"

Connected through hyperedge HE-4 (induced by source paper "separating decision tree complexity from subcube partition complexity"):
  with members:
    - "a composition theorem for decision tree complexity"
    - "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)