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: "local conflict coloring"
  Abstract: Locally finding a solution to symmetry-breaking tasks such as vertex-coloring, edge-coloring, maximal matching, maximal independent set, etc., is a long-standing challenge in distributed network computing. More recently, it has also become a challenge in the framework of centralized local computation. We introduce conflict coloring as a general symmetry-breaking task that includes all the aforementioned tasks as specific instantiations --- conflict coloring includes all locally checkable labeling tasks from [Naor\&Stockmeyer, STOC 1993]. Conflict coloring is characterized by two parameters $l$ and $d$, where the former measures the amount of freedom given to the nodes for selecting their colors, and the latter measures the number of constraints which colors of adjacent nodes are subject to.We show that, in the standard LOCAL model for distributed network computing, if $l/d \textgreater{} \Delta$, then conflict coloring can be solved in $\tilde O(\sqrt{\Delta})+\log^*n$ rounds in $n$-node graphs with maximum degree $\Delta$, where $\tilde O$ ignores the polylog factors in $\Delta$. The dependency in~$n$ is optimal, as a consequence of the $\Omega(\log^*n)$ lower bound by [Linial, SIAM J. Comp. 1992] for $(\Delta+1)$-coloring. An important special case of our result is a significant improvement over the best known algorithm for distributed $(\Delta+1)$-coloring due to [Barenboim, PODC 2015], which required $\tilde O(\Delta^{3/4})+\log^*n$ rounds. Improvements for other variants of coloring, including $(\Delta+1)$-list-coloring, $(2\Delta-1)$-edge-coloring, $T$-coloring, etc., also follow from our general result on conflict coloring. Likewise, in the framework of centralized local computation algorithms (LCAs), our general result yields an LCA which requires a smaller number of probes than the previously best known algorithm for vertex-coloring, and works for a wide range of coloring problems.

Connected through hyperedge HE-1 (induced by source paper "distributed edge coloring in time quasi polylogarithmic in delta"):
  with members:
    - "faster deterministic distributed coloring through recursive list coloring"
    - "polylogarithmic time deterministic network decomposition and distributed derandomization"
    - "towards the locality of vizing s theorem"
    - "distributed approximation algorithms for maximum matching in graphs and hypergraphs"
    - "the complexity of distributed edge coloring with small palettes"
    - "deterministic distributed edge coloring with fewer colors"
    - "deterministic distributed edge coloring via hypergraph maximal matching"
    - "on derandomizing local distributed algorithms"

Connected through hyperedge HE-2 (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"
    - "quadratic and near quadratic lower bounds for the congest model"

Connected through hyperedge HE-3 (induced by source paper "fast and simple deterministic algorithms for highly dynamic networks"):
  with members:
    - "lower bounds for maximal matchings and maximal independent sets"
    - "how much does randomness help with locally checkable problems"
    - "simple dynamic algorithms for maximal independent set and other problems"
    - "fully dynamic maximal independent set with sublinear update time"
    - "local distributed algorithms in highly dynamic networks"
    - "improved algorithms for fully dynamic maximal independent set"
    - "improved deterministic distributed matching via rounding"
    - "new classes of distributed time complexity"

Connected through hyperedge HE-4 (induced by source paper "faster deterministic distributed coloring through recursive list coloring"):
  with members:
    - "towards the locality of vizing s theorem"
    - "distributed approximation algorithms for maximum matching in graphs and hypergraphs"
    - "improved distributed delta coloring"
    - "the complexity of distributed edge coloring with small palettes"
    - "deterministic distributed edge coloring with fewer colors"
    - "deterministic distributed edge coloring via hypergraph maximal matching"
    - "adapting sequential algorithms to the distributed setting"
    - "on derandomizing local distributed algorithms"

Connected through hyperedge HE-5 (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"
    - "quadratic and near quadratic lower bounds for the congest model"
    - "adapting sequential algorithms to the distributed setting"

Connected through hyperedge HE-6 (induced by source paper "on the complexity of distributed splitting problems"):
  with members:
    - "improved distributed degree splitting and edge coloring"
    - "sublogarithmic distributed algorithms for lov asz local lemma and the complexity hierarchy"
    - "deterministic distributed edge coloring with fewer colors"
    - "deterministic distributed edge coloring via hypergraph maximal matching"
    - "a time hierarchy theorem for the local model"
    - "on derandomizing local distributed algorithms"
    - "distributed degree splitting edge coloring and orientations"
    - "an exponential separation between randomized and deterministic complexity in the local model"

Connected through hyperedge HE-7 (induced by source paper "graph coloring via degeneracy in streaming and other space conscious models"):
  with members:
    - "simple graph coloring algorithms for congested clique and massively parallel computation"
    - "greedy and local ratio algorithms in the mapreduce model"
    - "dynamic algorithms for graph coloring"
    - "dynamic graph coloring"
    - "simple and near optimal distributed coloring for sparse graphs"
    - "densest subgraph in dynamic graph streams"
    - "hypergraph two coloring in the streaming model"
    - "communication steps for parallel query processing"

Connected through hyperedge HE-8 (induced by source paper "a sharp threshold phenomenon for the distributed complexity of the lovasz local lemma"):
  with members:
    - "on the complexity of distributed splitting problems"
    - "polylogarithmic time deterministic network decomposition and distributed derandomization"
    - "distributed approximation algorithms for maximum matching in graphs and hypergraphs"
    - "improved distributed degree splitting and edge coloring"
    - "a time hierarchy theorem for the local model"
    - "on derandomizing local distributed algorithms"
    - "distributed degree splitting edge coloring and orientations"
    - "an exponential separation between randomized and deterministic complexity in the local 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.DS(Data Structures and Algorithms)