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 multi round communication lower bound for gap hamming and some consequences"
  Abstract: The Gap-Hamming-Distance problem arose in the context of proving space lower bounds for a number of key problems in the data stream model. In this problem, Alice and Bob have to decide whether the Hamming distance between their $n$-bit input strings is large (i.e., at least $n/2 + \sqrt n$) or small (i.e., at most $n/2 - \sqrt n$); they do not care if it is neither large nor small. This $\Theta(\sqrt n)$ gap in the problem specification is crucial for capturing the approximation allowed to a data stream algorithm. #R##N#Thus far, for randomized communication, an $\Omega(n)$ lower bound on this problem was known only in the one-way setting. We prove an $\Omega(n)$ lower bound for randomized protocols that use any constant number of rounds. #R##N#As a consequence we conclude, for instance, that $\epsilon$-approximately counting the number of distinct elements in a data stream requires $\Omega(1/\epsilon^2)$ space, even with multiple (a constant number of) passes over the input stream. This extends earlier one-pass lower bounds, answering a long-standing open question. We obtain similar results for approximating the frequency moments and for approximating the empirical entropy of a data stream. #R##N#In the process, we also obtain tight $n - \Theta(\sqrt{n}\log n)$ lower and upper bounds on the one-way deterministic communication complexity of the problem. Finally, we give a simple combinatorial proof of an $\Omega(n)$ lower bound on the one-way randomized communication complexity.

Connected through hyperedge HE-1 (induced by source paper "distributed data summarization in well connected networks"):
  with members:
    - "new distributed algorithms in almost mixing time via transformations from parallel algorithms"
    - "optimal gossip algorithms for exact and approximate quantile computations"
    - "streaming space complexity of nearly all functions of one variable on frequency vectors"
    - "taylor polynomial estimator for estimating frequency moments"
    - "tight bounds for lp samplers finding duplicates in streams and related problems"

Connected through hyperedge HE-2 (induced by source paper "optimal streaming and tracking distinct elements with high probability"):
  with members:
    - "streaming space complexity of nearly all functions of one variable on frequency vectors"
    - "explicit resilient functions matching ajtai linial"
    - "tracking the frequency moments at all times"

Connected through hyperedge HE-3 (induced by source paper "sketching and embedding are equivalent for norms"):
  with members:
    - "streaming symmetric norms via measure concentration"
    - "sketching as a tool for numerical linear algebra"
    - "an optimal lower bound on the communication complexity of gap hamming distance"
    - "optimal lower bounds for locality sensitive hashing except when q is tiny"
    - "better gap hamming lower bounds via better round elimination"
    - "planar earthmover is not in l_1"
    - "lower bounds on locality sensitive hashing"

Connected through hyperedge HE-4 (induced by source paper "arthur merlin streaming complexity"):
  with members:
    - "practical verified computation with streaming interactive proofs"
    - "streaming graph computations with a helpful advisor"
    - "an optimal lower bound on the communication complexity of gap hamming distance"
    - "rectangle size bounds and threshold covers in communication complexity"

Connected through hyperedge HE-5 (induced by source paper "on the communication complexity of sparse set disjointness and exists equal problems"):
  with members:
    - "recognizing well parenthesized expressions in the streaming model"
    - "better gap hamming lower bounds via better round elimination"
    - "a direct sum theorem in communication complexity via message compression"

Connected through hyperedge HE-6 (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"
    - "information complexity versus corruption and applications to orthogonality and gap hamming"
    - "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"

Connected through hyperedge HE-7 (induced by source paper "an optimal lower bound on the communication complexity of gap hamming distance"):
  with members:
    - "tight bounds for distributed functional monitoring"
    - "better gap hamming lower bounds via better round elimination"
    - "the partition bound for classical communication complexity and query complexity"
    - "a strong direct product theorem for disjointness"
    - "rectangle size bounds and threshold covers in communication complexity"

Connected through hyperedge HE-8 (induced by source paper "better gap hamming lower bounds via better round elimination"):
  with members:
    - "an optimal lower bound on the communication complexity of gap hamming distance"
    - "disjointness is hard in the multi party number on the forehead model"

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)