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: "the range of topological effects on communication"
  Abstract: We continue the study of communication cost of computing functions when inputs are distributed among $k$ processors, each of which is located at one vertex of a network/graph called a terminal. Every other node of the network also has a processor, with no input. The communication is point-to-point and the cost is the total number of bits exchanged by the protocol, in the worst case, on all edges. #R##N#Chattopadhyay, Radhakrishnan and Rudra (FOCS'14) recently initiated a study of the effect of topology of the network on the total communication cost using tools from $L_1$ embeddings. Their techniques provided tight bounds for simple functions like Element-Distinctness (ED), which depend on the 1-median of the graph. This work addresses two other kinds of natural functions. We show that for a large class of natural functions like Set-Disjointness the communication cost is essentially $n$ times the cost of the optimal Steiner tree connecting the terminals. Further, we show for natural composed functions like $\text{ED} \circ \text{XOR}$ and $\text{XOR} \circ \text{ED}$, the naive protocols suggested by their definition is optimal for general networks. Interestingly, the bounds for these functions depend on more involved topological parameters that are a combination of Steiner tree and 1-median costs. #R##N#To obtain our results, we use some new tools in addition to ones used in Chattopadhyay et. al. These include (i) viewing the communication constraints via a linear program; (ii) using tools from the theory of tree embeddings to prove topology sensitive direct sum results that handle the case of composed functions and (iii) representing the communication constraints of certain problems as a family of collection of multiway cuts, where each multiway cut simulates the hardness of computing the function on the star topology.

Connected through hyperedge HE-1 (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"
    - "it s all a matter of degree using degree information to optimize multiway joins"
    - "faq questions asked frequently"
    - "skew in parallel query processing"
    - "aggregation and ordering in factorised databases"

Connected through hyperedge HE-2 (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"
    - "tight bounds for set disjointness in the message passing model"
    - "information equals amortized communication"
    - "lower bounds for number in hand multiparty communication complexity made easy"
    - "tight bounds for distributed functional monitoring"
    - "distributed verification and hardness of distributed approximation"

Connected through hyperedge HE-3 (induced by source paper "multi party protocols information complexity and privacy"):
  with members:
    - "tribes is hard in the message passing model"
    - "tight bounds for set disjointness in the message passing model"
    - "information equals amortized communication"
    - "lower bounds for number in hand multiparty communication complexity made easy"
    - "distributed verification and hardness of distributed approximation"
    - "a strong direct product theorem for disjointness"
    - "a direct sum theorem in communication complexity via message compression"

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)