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 "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a log-factor approximation (Boros et al., Networks '14), and is fixed-parameter tractable in terms of~$k$ (Lokshtanov, unpublished '14).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.

Includes members:
  Member "bidimensionality and kernels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hitting topological minors is fpt")
  Member "on the complexity of the vector connectivity problem":
    also connected through other hyperedges:
      (none)
  Member "kernelization lower bounds by cross composition":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "subexponential parameterized algorithms and kernelization on almost chordal graphs")
  Member "kernels for connected dominating set on graphs with excluded topological subgraphs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a general kernelization technique for domination and independence problems in sparse classes")
  Member "designing fpt algorithms for cut problems using randomized contractions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "grundy coloring friends half graphs bicliques")
  Member "linear kernels and single exponential algorithms via protrusion decompositions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "hitting topological minors is fpt")
  Member "representative sets and irrelevant vertices new tools for kernelization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on quasipolynomial multicut mimicking networks and kernelization of multiway cut problems")
  Member "finding small separators in linear time via treewidth reduction":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "fixed parameter tractability of counting small minimum s t cuts")

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.CC(Computational Complexity)