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: "on kernelization and approximation for the vector connectivity problem"
  Abstract: In the Vector Connectivity problem we are given an undirected graph $G=(V,E)$, a demand function $\phi\colon V\to\{0,\ldots,d\}$, and an integer $k$. The question is whether there exists a set $S$ of at most $k$ vertices such that every vertex $v\in V\setminus S$ has at least $\phi(v)$ vertex-disjoint paths to $S$; this abstractly captures questions about placing servers or warehouses relative to demands. The problem is \NP-hard already for instances with $d=4$ (Cicalese et al., arXiv '14), admits a log-factor approximation (Boros et al., Networks '14), and is fixed-parameter tractable in terms of~$k$ (Lokshtanov, unpublished '14). We prove several results regarding kernelization and approximation for Vector Connectivity and the variant Vector $d$-Connectivity where the upper bound $d$ on demands is a fixed constant. For Vector $d$-Connectivity we give a factor $d$-approximation algorithm and construct a vertex-linear kernelization, i.e., an efficient reduction to an equivalent instance with $f(d)k=O(k)$ vertices. For Vector Connectivity we have a factor $\text{opt}$-approximation and we can show that it has no kernelization to size polynomial in $k$ or even $k+d$ unless $\mathsf{NP\subseteq coNP/poly}$, making $f(d)\operatorname{poly}(k)$ optimal for Vector $d$-Connectivity. Finally, we provide a write-up for fixed-parameter tractability of Vector Connectivity($k$) by giving an alternative FPT algorithm based on matroid intersection.

Connected through hyperedge HE-1 (induced by source paper "on the complexity of the vector connectivity problem"):
  with members:
    - "latency bounded target set selection in social networks"
    - "on the approximability and exact algorithms for vector domination and related problems in graphs"

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.CC(Computational Complexity)