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: "fast distributed approximation for tap and 2 edge connectivity"
  Abstract: The tree augmentation problem (TAP) is a fundamental network design problem, in which the input is a graph $G$ and a spanning tree $T$ for it, and the goal is to augment $T$ with a minimum set of edges $Aug$ from $G$, such that $T \cup Aug$ is 2-edge-connected. #R##N#TAP has been widely studied in the sequential setting. The best known approximation ratio of 2 for the weighted case dates back to the work of Frederickson and J\'{a}J\'{a}, SICOMP 1981. Recently, a 3/2-approximation was given for the unweighted case by Kortsarz and Nutov, TALG 2016, and recent breakthroughs by Adjiashvili, SODA 2017, and by Fiorini et al., 2017, give approximations better than 2 for bounded weights. #R##N#In this paper, we provide the first fast distributed approximations for TAP. We present a distributed $2$-approximation for weighted TAP which completes in $O(h)$ rounds, where $h$ is the height of $T$. When $h$ is large, we show a much faster 4-approximation algorithm for the unweighted case, completing in $O(D+\sqrt{n}\log^*{n})$ rounds, where $n$ is the number of vertices and $D$ is the diameter of $G$. #R##N#Immediate consequences of our results are an $O(D)$-round 2-approximation algorithm for the minimum size 2-edge-connected spanning subgraph, which significantly improves upon the running time of previous approximation algorithms, and an $O(h_{MST}+\sqrt{n}\log^{*}{n})$-round 3-approximation algorithm for the weighted case, where $h_{MST}$ is the height of the MST of the graph. Additional applications are algorithms for verifying 2-edge-connectivity and for augmenting the connectivity of any connected spanning subgraph to 2. #R##N#Finally, we complement our study with proving lower bounds for distributed approximations of TAP.

Connected through hyperedge HE-1 (induced by source paper "hardness of distributed optimization"):
  with members:
    - "small cuts and connectivity certificates a fault tolerant approach"
    - "fast and efficient distributed computation of hamiltonian cycles in random graphs"
    - "a distributed algorithm for finding hamiltonian cycles in random graphs in o log n time"
    - "new distributed algorithms in almost mixing time via transformations from parallel algorithms"
    - "parameterized distributed algorithms"
    - "distributed exact weighted all pairs shortest paths in near linear time"
    - "detecting cliques in congest networks"
    - "simple and local independent set approximation"

Connected through hyperedge HE-2 (induced by source paper "small cuts and connectivity certificates a fault tolerant approach"):
  with members:
    - "deterministic combinatorial replacement paths and distance sensitivity oracles"
    - "distributed edge connectivity in sublinear time"
    - "polylogarithmic time deterministic network decomposition and distributed derandomization"
    - "low congestion cycle covers and their applications"
    - "distributed approximation of minimum k edge connected spanning subgraphs"
    - "almost tight distributed minimum cut algorithms"
    - "distributed minimum cut approximation"
    - "fault tolerant spanners better and simpler"

Connected through hyperedge HE-3 (induced by source paper "improved distributed approximations for minimum weight two edge connected spanning subgraph"):
  with members:
    - "distributed edge connectivity in sublinear time"
    - "small cuts and connectivity certificates a fault tolerant approach"
    - "minor excluded network families admit fast distributed algorithms"
    - "new distributed algorithms in almost mixing time via transformations from parallel algorithms"
    - "distributed approximation of minimum k edge connected spanning subgraphs"
    - "low congestion shortcuts without embedding"
    - "almost tight distributed minimum cut algorithms"
    - "distributed minimum cut approximation"

Connected through hyperedge HE-4 (induced by source paper "distributed approximation of minimum k edge connected spanning subgraphs"):
  with members:
    - "distributed spanner approximation"
    - "a simple deterministic distributed mst algorithm with near optimal time and message complexities"
    - "a time and message optimal distributed algorithm for minimum spanning trees"
    - "almost tight distributed minimum cut algorithms"
    - "distributed minimum cut approximation"
    - "distributed connectivity decomposition"
    - "distributed verification and hardness of distributed approximation"
    - "local computation lower and upper bounds"

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)