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: "quadratic and near quadratic lower bounds for the congest model"
  Abstract: We present the first super-linear lower bounds for natural graph problems in the CONGEST model, answering a long-standing open question. #R##N#Specifically, we show that any exact computation of a minimum vertex cover or a maximum independent set requires $\Omega(n^2/\log^2{n})$ rounds in the worst case in the CONGEST model, as well as any algorithm for $\chi$-coloring a graph, where $\chi$ is the chromatic number of the graph. We further show that such strong lower bounds are not limited to NP-hard problems, by showing two simple graph problems in P which require a quadratic and near-quadratic number of rounds. #R##N#Finally, we address the problem of computing an exact solution to weighted all-pairs-shortest-paths (APSP), which arguably may be considered as a candidate for having a super-linear lower bound. We show a simple $\Omega(n)$ lower bound for this problem, which implies a separation between the weighted and unweighted cases, since the latter is known to have a complexity of $\Theta(n/\log{n})$. We also formally prove that the standard Alice-Bob framework is incapable of providing a super-linear lower bound for exact weighted APSP, whose complexity remains an intriguing open question.

Connected through hyperedge HE-1 (induced by source paper "distributed maximum matching verification in congest"):
  with members:
    - "lower bounds for maximal matchings and maximal independent sets"
    - "sparsifying distributed algorithms with ramifications in massively parallel computation and centralized local computation"
    - "improved deterministic distributed matching via rounding"
    - "coresets meet edcs algorithms for matching and vertex cover on massive graphs"
    - "round compression for parallel matching algorithms"
    - "deterministic distributed edge coloring via hypergraph maximal matching"
    - "on derandomizing local distributed algorithms"
    - "distributed approximation of maximum independent set and maximum matching"

Connected through hyperedge HE-2 (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"
    - "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"
    - "approximation of distances and shortest paths in the broadcast congest clique"

Connected through hyperedge HE-3 (induced by source paper "simple and fast distributed computation of betweenness centrality"):
  with members:
    - "distributed estimation and control of node centrality in undirected asymmetric networks"
    - "distributed algorithms for directed betweenness centrality and all pairs shortest paths"
    - "distributed exact weighted all pairs shortest paths in near linear time"
    - "distributed algorithms for computation of centrality measures in complex networks"
    - "abra approximating betweenness centrality in static and dynamic graphs with rademacher averages"
    - "fully dynamic approximation of betweenness centrality"
    - "scalable online betweenness centrality in evolving graphs"
    - "approximating betweenness centrality in large evolving networks"

Connected through hyperedge HE-4 (induced by source paper "distributed edge connectivity in sublinear time"):
  with members:
    - "improved distributed expander decomposition and nearly optimal triangle enumeration"
    - "small cuts and connectivity certificates a fault tolerant approach"
    - "distributed triangle detection via expander decomposition"
    - "graph sparsification spectral sketches and faster resistance computation via short cycle decompositions"
    - "distributed exact weighted all pairs shortest paths in near linear time"
    - "expander decomposition and pruning faster stronger and simpler"
    - "a faster distributed single source shortest paths algorithm"
    - "distributed exact shortest paths in sublinear time"

Connected through hyperedge HE-5 (induced by source paper "what graph neural networks cannot learn depth vs width"):
  with members:
    - "edgenets edge varying graph neural networks"
    - "universal invariant and equivariant graph neural networks"
    - "lanczosnet multi scale deep graph convolutional networks"
    - "mincut pooling in graph neural networks"
    - "break the ceiling stronger multi scale deep graph convolutional networks"
    - "understanding the representation power of graph neural networks in learning graph topology"
    - "on the universality of invariant networks"
    - "approximation ratios of graph neural networks for combinatorial problems"

Connected through hyperedge HE-6 (induced by source paper "smaller cuts higher lower bounds"):
  with members:
    - "a faster deterministic distributed algorithm for weighted apsp through pipelining"
    - "a deterministic distributed algorithm for exact weighted all pairs shortest paths in tilde o n 3 2 rounds"
    - "distributed exact weighted all pairs shortest paths in near linear time"
    - "optimal distributed coloring algorithms for planar graphs in the local model"
    - "distributed exact shortest paths in sublinear time"
    - "a time hierarchy theorem for the local model"
    - "a 2 ϵ approximation for maximum weight matching in the semi streaming model"
    - "distributed approximation of maximum independent set and maximum matching"

Connected through hyperedge HE-7 (induced by source paper "hardness of distributed optimization"):
  with members:
    - "small cuts and connectivity certificates a fault tolerant approach"
    - "fast and efficient distributed computation of hamiltonian cycles in random graphs"
    - "a distributed algorithm for finding hamiltonian cycles in random graphs in o log n time"
    - "new distributed algorithms in almost mixing time via transformations from parallel algorithms"
    - "parameterized distributed algorithms"
    - "distributed exact weighted all pairs shortest paths in near linear time"
    - "detecting cliques in congest networks"
    - "simple and local independent set approximation"

Connected through hyperedge HE-8 (induced by source paper "efficient deterministic distributed coloring with small bandwidth"):
  with members:
    - "faster deterministic distributed coloring through recursive list coloring"
    - "on the use of randomness in local distributed graph algorithms"
    - "deterministic distributed dominating set approximation in the congest model"
    - "delta 1 coloring in the congested clique model"
    - "local distributed algorithms in highly dynamic networks"
    - "the complexity of delta 1 coloring incongested clique massively parallel computation and centralized local computation"
    - "adapting sequential algorithms to the distributed setting"
    - "on derandomizing local distributed algorithms"

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.DC(Distributed, Parallel, and Cluster Computing)