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: "cover and conquer augmenting decompositions for connectivity problems"
  Abstract: We explore and introduce tools to design algorithms with improved approximation guarantees for edge connectivity problems such as the traveling salesman problem (TSP) and the 2-edge-connected spanning multigraph problem (2EC) on (restricted classes of) weighted graphs. In particular, we investigate decompositions of graphs that cover small-cardinality cuts an even number of times. Such decompositions allow us to design approximation algorithms that consist of augmenting an initial subgraph (e.g. cycle cover or spanning tree) with a cheap addition to form a feasible solution. Boyd, Iwata and Takazawa recently presented an algorithm to find a cycle cover that covers all 3- and 4-edge cuts in a bridgeless, cubic graph with applications to 2EC on 3-edge-connected, cubic graphs [BIT 2013]. We present several applications of their algorithm to connectivity problems on node-weighted graphs, which has been suggested as an intermediate step between graph and general metrics. Specifically, on 3-edge-connected, cubic, node-weighted graphs, we present a $\frac{7}{5}$-approximation algorithm for TSP and a $\frac{13}{10}$-approximation algorithm for 2EC. Moreover, we use a cycle cover that covers all 3- and 4-edge cuts to show that the everywhere $\frac{18}{19}$ vector is a convex combination of incidence vectors of tours, answering a question of Seb{\H{o}}. #R##N#Extending this approach to input graphs that are 2-edge connected necessitates finding methods for covering 2-edge cuts. We therefore present a procedure to decompose an optimal solution for the subtour linear program into spanning, connected subgraphs that cover each 2-edge cut an even number of times. We use this decomposition to design a simple $\frac{4}{3}$-approximation algorithm for the 2-edge connected problem on subcubic, node-weighted graphs.

Connected through hyperedge HE-1 (induced by source paper "an improved approximation algorithm for tsp in the half integral case"):
  with members:
    - "towards improving christofides algorithm for half integer tsp"
    - "improved inapproximability for tsp"
    - "13 9 approximation for graphic tsp"

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)