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 "faster deterministic distributed coloring through recursive list coloring"):
  Abstract: We provide novel deterministic distributed vertex coloring algorithms. As our main result, we give a deterministic distributed algorithm to compute a $(\Delta+1)$-coloring of an $n$-node graph with maximum degree $\Delta$ in $2^{O(\sqrt{\log\Delta})}\cdot\log n$ rounds. This improves on the best previously known time complexity for a large range of values of $\Delta$. For graphs with arboricity $a$, we obtain a deterministic distributed algorithm to compute a $(2+o(1))a$-coloring in time $2^{O(\sqrt{\log a})}\cdot\log^2 n$. Further, for graphs with bounded neighborhood independence, we show that a $(\Delta+1)$-coloring can be computed more efficiently in time $2^{O(\sqrt{\log\Delta})} + O(\log^* n)$. This in particular implies that also a $(2\Delta-1)$-edge coloring can be computed deterministically in $2^{O(\sqrt{\log\Delta})} + O(\log^* n)$ rounds, which improves the best known time bound for small values of $\Delta$. All results even hold for the list coloring variants of the problems. As a consequence, we also obtain an improved deterministic $2^{O(\sqrt{\log\Delta})}\cdot\log^3 n$-round algorithm for $\Delta$-coloring non-complete graphs with maximum degree $\Delta\geq 3$. Most of our algorithms only require messages of $O(\log n)$ bits (including the $(\Delta+1)$-vertex coloring algorithms). #R##N#Our main technical contribution is a recursive deterministic distributed list coloring algorithm to solve list coloring problems with lists of size $\Delta^{1+o(1)}$. Given some list coloring problem and an orientation of the edges, we show how to recursively divide the global color space into smaller subspaces, assign one of the subspaces to each node of the graph, and compute a new edge orientation such that for each node, the list size to out-degree ratio degrades at most by a constant factor on each recursion level.

Includes members:
  Member "towards the locality of vizing s theorem":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distributed edge coloring in time quasi polylogarithmic in delta")
  Member "distributed approximation algorithms for maximum matching in graphs and hypergraphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "distributed edge coloring in time quasi polylogarithmic in delta")
  Member "improved distributed delta coloring":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "locality of not so weak coloring")
  Member "the complexity of distributed edge coloring with small palettes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "distributed edge coloring in time quasi polylogarithmic in delta")
  Member "deterministic distributed edge coloring with fewer colors":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "distributed edge coloring in time quasi polylogarithmic in delta")
  Member "deterministic distributed edge coloring via hypergraph maximal matching":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "distributed maximum matching verification in congest")
  Member "adapting sequential algorithms to the distributed setting":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "hardness of distributed optimization")
  Member "on derandomizing local distributed algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "distributed maximum matching verification 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.DS(Data Structures and Algorithms)