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 "distributed minimum vertex coloring and maximum independent set in chordal graphs"):
  Abstract: We give deterministic distributed $(1+\epsilon)$-approximation algorithms for Minimum Vertex Coloring and Maximum Independent Set on chordal graphs in the LOCAL model. Our coloring algorithm runs in $O(\frac{1}{\epsilon} \log n)$ rounds, and our independent set algorithm has a runtime of $O(\frac{1}{\epsilon}\log(\frac{1}{\epsilon})\log^* n)$ rounds. For coloring, existing lower bounds imply that the dependencies on $\frac{1}{\epsilon}$ and $\log n$ are best possible. For independent set, we prove that $O(\frac{1}{\epsilon})$ rounds are necessary. #R##N#Both our algorithms make use of a tree decomposition of the input chordal graph. They iteratively peel off interval subgraphs, which are identified via the tree decomposition of the input graph, thereby partitioning the vertex set into $O(\log n)$ layers. For coloring, each interval graph is colored independently, which results in various coloring conflicts between the layers. These conflicts are then resolved in a separate phase, using the particular structure of our partitioning. For independent set, only the first $O( \log \frac{1}{\epsilon})$ layers are required as they already contain a large enough independent set. We develop a $(1+\epsilon)$-approximation maximum independent set algorithm for interval graphs, which we then apply to those layers. #R##N#This work raises the question as to how useful tree decompositions are for distributed computing.

Includes members:
  Member "simple and near optimal distributed coloring for sparse graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "graph coloring via degeneracy in streaming and other space conscious models")
  Member "on the complexity of local distributed graph problems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "distributed edge coloring in time quasi polylogarithmic in delta")
  Member "a fast network decomposition algorithm and its applications to constant time distributed computation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "message reduction in the local model is a free lunch")
  Member "an improved distributed algorithm for maximal independent set":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "space efficient approximation to maximum matching size from uniform edge samples")
  Member "the locality of distributed symmetry breaking":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "distributed maximum matching verification in congest")
  Member "on the locality of some np complete problems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "smaller cuts higher lower bounds")

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)