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: "lower bounds for number in hand multiparty communication complexity made easy"
  Abstract: In this paper we prove lower bounds on randomized multiparty communication complexity, both in the \emph{blackboard model} (where each message is written on a blackboard for all players to see) and (mainly) in the \emph{message-passing model}, where messages are sent player-to-player. We introduce a new technique for proving such bounds, called \emph{symmetrization}, which is natural, intuitive, and often easy to use. #R##N#For example, for the problem where each of $k$ players gets a bit-vector of length $n$, and the goal is to compute the coordinate-wise XOR of these vectors, we prove a tight lower bounds of $\Omega(nk)$ in the blackboard model. For the same problem with AND instead of XOR, we prove a lower bounds of roughly $\Omega(nk)$ in the message-passing model (assuming $k \le n/3200$) and $\Omega(n \log k)$ in the blackboard model. We also prove lower bounds for bit-wise majority, for a graph-connectivity problem, and for other problems; the technique seems applicable to a wide range of other problems as well. All of our lower bounds allow randomized communication protocols with two-sided error. #R##N#We also use the symmetrization technique to prove several direct-sum-like results for multiparty communication.

Connected through hyperedge HE-1 (induced by source paper "beyond alice and bob improved inapproximability for maximum independent set in congest"):
  with members:
    - "improved distributed approximation to maximum independent set"
    - "detecting cliques in congest networks"
    - "distributed spanner approximation"
    - "fooling views a new lower bound technique for distributed computations under congestion"
    - "quadratic and near quadratic lower bounds for the congest model"
    - "distributed approximation of maximum independent set and maximum matching"
    - "near linear lower bounds for distributed distance computations even in sparse networks"
    - "distributed construction of purely additive spanners"

Connected through hyperedge HE-2 (induced by source paper "the communication complexity of optimization"):
  with members:
    - "distributed and streaming linear programming in low dimensions"
    - "solving linear programs in the current matrix multiplication time"
    - "leveraging well conditioned bases streaming distributed summaries in minkowski p norms"
    - "distributed statistical estimation of matrix products with applications"
    - "l1 regression using lewis weights preconditioning and stochastic gradient descent"
    - "on communication complexity of classification problems"
    - "communication optimal distributed clustering"
    - "distributed low rank approximation of implicit functions of a matrix"

Connected through hyperedge HE-3 (induced by source paper "topology dependent bounds for faqs"):
  with members:
    - "query to communication lifting for bpp"
    - "juggling functions inside a database"
    - "worst case optimal algorithms for parallel query processing"
    - "tight network topology dependent bounds on rounds of communication"
    - "the range of topological effects on communication"
    - "it s all a matter of degree using degree information to optimize multiway joins"
    - "faq questions asked frequently"
    - "skew in parallel query processing"

Connected through hyperedge HE-4 (induced by source paper "a new approach to multi party peer to peer communication complexity"):
  with members:
    - "towards a complexity theory for the congested clique"
    - "multi party protocols information complexity and privacy"
    - "the range of topological effects on communication"
    - "tight bounds for set disjointness in the message passing model"
    - "information equals amortized communication"
    - "tight bounds for distributed functional monitoring"
    - "distributed verification and hardness of distributed approximation"

Connected through hyperedge HE-5 (induced by source paper "distributed and streaming linear programming in low dimensions"):
  with members:
    - "tight bounds for single pass streaming complexity of the set cover problem"
    - "communication steps for parallel query processing"
    - "efficient protocols for distributed classification and optimization"
    - "sorting searching and simulation in the mapreduce framework"
    - "linear programming in the semi streaming model with application to the maximum matching problem"
    - "lower bounds for predecessor searching in the cell probe model"

Connected through hyperedge HE-6 (induced by source paper "graph spanners in the message passing model"):
  with members:
    - "the 4 3 additive spanner exponent is tight"
    - "distributed computation of large scale graph problems"
    - "when distributed computation is communication expensive"
    - "tight bounds for distributed functional monitoring"

Connected through hyperedge HE-7 (induced by source paper "tight bounds on the round complexity of the distributed maximum coverage problem"):
  with members:
    - "distributed partial clustering"
    - "tight space approximation tradeoff for the multi pass streaming set cover problem"
    - "on estimating maximum matching size in graph streams"
    - "combinatorial auctions do need modest interaction"
    - "submodular optimization over sliding windows"
    - "distributed coverage maximization via sketching"
    - "almost optimal streaming algorithms for coverage problems"
    - "better streaming algorithms for the maximum coverage problem"

Connected through hyperedge HE-8 (induced by source paper "communication optimal distributed dynamic graph clustering"):
  with members:
    - "communication optimal distributed clustering"
    - "online row sampling"
    - "partitioning well clustered graphs spectral clustering works"
    - "iterative row sampling"

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)