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: "distributed approximation algorithms for maximum matching in graphs and hypergraphs"
  Abstract: We describe randomized and deterministic approximation algorithms in Linial's classic LOCAL model of distributed computing to find maximum-weight matchings in hypergraphs. For a rank-$r$ hypergraph, our algorithm generates a matching within an $O(r)$ factor of the maximum weight matching. The runtime is $\tilde O(\log r \log \Delta)$ for the randomized algorithm and $\tilde O(r \log \Delta + \log^3 \Delta)$ for the deterministic algorithm. #R##N#The randomized algorithm is a straightforward, though somewhat delicate, combination of an LP solver algorithm of Kuhn, Moscibroda \& Wattenhofer (2006) and randomized rounding. For the deterministic part, we extend a method of Ghaffari, Harris & Kuhn (2017) to derandomize the first-moment method; this allows us to deterministically simulate an alteration-based probabilistic construction. #R##N#This hypergraph matching algorithm has two main algorithmic consequences. First, we get nearly-optimal deterministic and randomized algorithms for the long-studied problem of maximum-weight graph matching. Specifically, we obtain a $1+\epsilon$ approximation algorithm running in $\tilde O(\log \Delta)$ randomized time and $\tilde O(\log^3 \Delta + \log^* n)$ deterministic time. These are significantly faster than prior $1+\epsilon$-approximation algorithms; furthermore, there are no constraints on the size of the edge weights. #R##N#Second, we get an algorithm for hypergraph maximal matching, which is significantly faster than the algorithm of Ghaffari, Harris & Kuhn (2017). One main consequence (along with some additional optimizations) is an algorithm which takes an arboricity-$a$ graph and generates an edge-orientation with out-degree $\lceil (1+\epsilon) a \rceil$; this runs in $\tilde O(\log^7 n \log^3 a)$ rounds deterministically or $\tilde O(\log^3 n )$ rounds randomly.

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"
    - "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"
    - "distributed degree splitting edge coloring and orientations"

Connected through hyperedge HE-2 (induced by source paper "faster deterministic distributed coloring through recursive list coloring"):
  with members:
    - "towards the locality of vizing s theorem"
    - "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"
    - "polynomial lower bound for distributed graph coloring in a weak local model"

Connected through hyperedge HE-3 (induced by source paper "distributed dense subgraph detection and low outdegree orientation"):
  with members:
    - "near optimal fully dynamic densest subgraph"
    - "improved distributed expander decomposition and nearly optimal triangle enumeration"
    - "improved deterministic distributed matching via rounding"
    - "improved distributed degree splitting and edge coloring"
    - "on derandomizing local distributed algorithms"
    - "distributed degree splitting edge coloring and orientations"
    - "densest subgraph in dynamic graph streams"
    - "applications of uniform sampling densest subgraph and beyond"

Connected through hyperedge HE-4 (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"
    - "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"
    - "on the complexity of local distributed graph problems"

Connected through hyperedge HE-5 (induced by source paper "deterministic distributed dominating set approximation in the congest model"):
  with members:
    - "delta 1 coloring in the congested clique model"
    - "congested clique algorithms for graph spanners"
    - "locally iterative distributed delta 1 coloring below szegedy vishwanathan barrier and applications to self stabilization and to restricted bandwidth models"
    - "adapting sequential algorithms to the distributed setting"
    - "on derandomizing local distributed algorithms"
    - "derandomizing local distributed algorithms under bandwidth restrictions"
    - "on the complexity of local distributed graph problems"
    - "a deterministic almost tight distributed algorithm for approximating single source shortest paths"

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

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)