human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "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.

Includes members:
  Member "tribes is hard in the message passing model":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "polynomial pass lower bounds for graph streaming algorithms")
  Member "on the communication complexity of linear algebraic problems in the message passing model":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "tight bounds for the subspace sketch problem with applications")
  Member "communication steps for parallel query processing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "equivalence classes and conditional hardness in massively parallel computations")
  Member "when distributed computation is communication expensive":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the communication complexity of optimization")
  Member "tight bounds for set disjointness in the message passing model":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "topology dependent bounds for faqs")
  Member "optimal deterministic routing and sorting on the congested clique":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "exponentially faster shortest paths in the congested clique")
  Member "distributed learning communication complexity and privacy":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a survey on distributed machine learning")
  Member "lower bounds for number in hand multiparty communication complexity made easy":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "beyond alice and bob improved inapproximability for maximum independent set in congest")

Question: Please tell me which class the source paper 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)