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: "near optimal distributed approximation of minimum weight connected dominating set"
  Abstract: This paper presents a near-optimal distributed approximation algorithm for the minimum-weight connected dominating set (MCDS) problem. The presented algorithm finds an $O(\log n)$ approximation in $\tilde{O}(D+\sqrt{n})$ rounds, where $D$ is the network diameter and $n$ is the number of nodes. #R##N#MCDS is a classical NP-hard problem and the achieved approximation factor $O(\log n)$ is known to be optimal up to a constant factor, unless P=NP. Furthermore, the $\tilde{O}(D+\sqrt{n})$ round complexity is known to be optimal modulo logarithmic factors (for any approximation), following [Das Sarma et al.---STOC'11].

Connected through hyperedge HE-1 (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"
    - "distributed approximation algorithms for maximum matching in graphs and hypergraphs"
    - "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"

Connected through hyperedge HE-2 (induced by source paper "distributed spanner approximation"):
  with members:
    - "distributed approximation of minimum k edge connected spanning subgraphs"
    - "improved deterministic distributed construction of spanners"
    - "distributed property testing for subgraph freeness revisited"
    - "quadratic and near quadratic lower bounds for the congest model"
    - "on derandomizing local distributed algorithms"
    - "distributed distance bounded network design through distributed convex programming"
    - "near linear lower bounds for distributed distance computations even in sparse networks"
    - "efficient algorithms for constructing very sparse spanners and emulators"

Connected through hyperedge HE-3 (induced by source paper "round and message optimal distributed graph algorithms"):
  with members:
    - "minor excluded network families admit fast distributed algorithms"
    - "a simple deterministic distributed mst algorithm with near optimal time and message complexities"
    - "low congestion shortcuts without embedding"
    - "a time and message optimal distributed algorithm for minimum spanning trees"
    - "near optimal distributed maximum flow"
    - "fast partial distance estimation and applications"
    - "almost tight distributed minimum cut algorithms"
    - "distributed approximation algorithms for weighted shortest paths"

Connected through hyperedge HE-4 (induced by source paper "a faster distributed single source shortest paths algorithm"):
  with members:
    - "a deterministic distributed algorithm for exact weighted all pairs shortest paths in tilde o n 3 2 rounds"
    - "faster distributed shortest path approximations via shortcuts"
    - "distributed exact shortest paths in sublinear time"
    - "improved distributed algorithms for exact shortest paths"
    - "a simple deterministic distributed mst algorithm with near optimal time and message complexities"
    - "distributed approximation of maximum independent set and maximum matching"
    - "parallel shortest paths using radius stepping"
    - "near optimal approximate shortest paths and transshipment in distributed and streaming models"

Connected through hyperedge HE-5 (induced by source paper "distributed symmetry breaking in hypergraphs"):
  with members:
    - "on computing maximal independent sets of hypergraphs in parallel"
    - "sublinear bounds for randomized leader election"
    - "distributed verification and hardness of distributed approximation"
    - "local computation lower and upper bounds"

Connected through hyperedge HE-6 (induced by source paper "can quantum communication speed up distributed computation"):
  with members:
    - "almost tight distributed minimum cut algorithms"
    - "distributed approximation algorithms for weighted shortest paths"
    - "brief announcement almost tight approximation distributed algorithm for minimum cut"
    - "distributed minimum cut approximation"
    - "distributed computation of sparse cuts"
    - "distributed connectivity decomposition"
    - "distributed random walks"
    - "distributed verification and hardness of distributed approximation"

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)