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 space efficiency of algorithms working on structural decompositions of graphs"
  Abstract: Dynamic programming on path and tree decompositions of graphs is a technique that is ubiquitous in the field of parameterized and exponential-time algorithms. However, one of its drawbacks is that the space usage is exponential in the decomposition's width. Following the work of Allender et al. [Theory of Computing, '14], we investigate whether this space complexity explosion is unavoidable. Using the idea of reparameterization of Cai and Juedes [J. Comput. Syst. Sci., '03], we prove that the question is closely related to a conjecture that the Longest Common Subsequence problem parameterized by the number of input strings does not admit an algorithm that simultaneously uses XP time and FPT space. Moreover, we complete the complexity landscape sketched for pathwidth and treewidth by Allender et al. by considering the parameter tree-depth. We prove that computations on tree-depth decompositions correspond to a model of non-deterministic machines that work in polynomial time and logarithmic space, with access to an auxiliary stack of maximum height equal to the decomposition's depth. Together with the results of Allender et al., this describes a hierarchy of complexity classes for polynomial-time non-deterministic machines with different restrictions on the access to working space, which mirrors the classic relations between treewidth, pathwidth, and tree-depth.

Connected through hyperedge HE-1 (induced by source paper "hamiltonian cycle parameterized by treedepth in single exponential time and polynomial space"):
  with members:
    - "solving connectivity problems parameterized by treedepth in single exponential time and polynomial space"
    - "improved bounds for the excluded minor approximation of treedepth"
    - "polynomial bounds for centered colorings on proper minor closed graph classes"
    - "fast exact algorithms for some connectivity problems parametrized by clique width"
    - "turing kernelization for finding long paths in graph classes excluding a topological minor"
    - "clifford algebras meet tree decompositions"
    - "a faster parameterized algorithm for treedepth"
    - "fast hamiltonicity checking via bases of perfect matchings"

Connected through hyperedge HE-2 (induced by source paper "polynomial bounds for centered colorings on proper minor closed graph classes"):
  with members:
    - "experimental evaluation of counting subgraph isomorphisms in classes of bounded expansion"
    - "planar subgraph isomorphism revisited"
    - "optimally cutting a surface into a disk"
    - "subgraph isomorphism in planar graphs and related problems"

Connected through hyperedge HE-3 (induced by source paper "space efficient algorithms for longest increasing subsequence"):
  with members:
    - "improved time space trade offs for computing voronoi diagrams"
    - "estimating the longest increasing sequence in polylogarithmic time"
    - "space efficient streaming algorithms for the distance to monotonicity and asymmetric edit distance"

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)