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: "label cover instances with large girth and the hardness of approximating basic k spanner"
  Abstract: We study the well-known Label Cover problem under the additional requirement that problem instances have large girth. We show that if the girth is some $k$, the problem is roughly $2^{\log^{1-\epsilon} n/k}$ hard to approximate for all constant $\epsilon > 0$. A similar theorem was claimed by Elkin and Peleg [ICALP 2000], but their proof was later found to have a fundamental error. We use the new proof to show inapproximability for the basic $k$-spanner problem, which is both the simplest problem in graph spanners and one of the few for which super-logarithmic hardness was not known. Assuming $NP \not\subseteq BPTIME(2^{polylog(n)})$, we show that for every $k \geq 3$ and every constant $\epsilon > 0$ it is hard to approximate the basic $k$-spanner problem within a factor better than $2^{(\log^{1-\epsilon} n) / k}$ (for large enough $n$). A similar hardness for basic $k$-spanner was claimed by Elkin and Peleg [ICALP 2000], but the error in their analysis of Label Cover made this proof fail as well. Thus for the problem of Label Cover with large girth we give the first non-trivial lower bound. For the basic $k$-spanner problem we improve the previous best lower bound of $\Omega(\log n)/k$ by Kortsarz [Algorithmica 1998]. Our main technique is subsampling the edges of 2-query PCPs, which allows us to reduce the degree of a PCP to be essentially equal to the soundness desired. This turns out to be enough to essentially guarantee large girth.

Connected through hyperedge HE-1 (induced by source paper "graph spanners a tutorial review"):
  with members:
    - "near additive spanners and near exact hopsets a unified view"
    - "some general structure for extremal sparsification problems"
    - "weighted additive spanners"
    - "near additive spanners in low polynomial deterministic congest time"
    - "multi level graph sketches via single level solvers"
    - "almost shortest paths and pram distance oracles in weighted graphs"
    - "an fpt algorithm for minimum additive spanner problem"
    - "distributed construction of light networks"

Connected through hyperedge HE-2 (induced by source paper "lasserre integrality gaps for graph spanners and related problems"):
  with members:
    - "characterizing demand graphs for fixed parameter shallow light steiner network"
    - "approximating spanners and directed steiner forest upper and lower bounds"
    - "parallel metric tree embedding based on an algebraic view on moore bellman ford"
    - "everywhere sparse spanners via dense subgraphs"
    - "rounding semidefinite programming hierarchies via global correlation"
    - "fault tolerant spanners better and simpler"
    - "directed steiner tree and the lasserre hierarchy"
    - "directed spanners via flow based linear programs"

Connected through hyperedge HE-3 (induced by source paper "the norms of graph spanners"):
  with members:
    - "sherali adams integrality gaps matching the log density threshold"
    - "the greedy spanner is existentially optimal"
    - "minimizing the union tight approximations for small set bipartite vertex expansion"
    - "fault tolerant spanners better and simpler"
    - "directed spanners via flow based linear programs"
    - "transitive closure spanners"

Connected through hyperedge HE-4 (induced by source paper "multi level graph sketches via single level solvers"):
  with members:
    - "the sparsest additive spanner via multiple weighted bfs trees"
    - "on pairwise spanners"
    - "approximating subset k connectivity problems"

Connected through hyperedge HE-5 (induced by source paper "distributed spanner approximation"):
  with members:
    - "distributed approximation of minimum k edge connected spanning subgraphs"
    - "improved deterministic distributed construction of spanners"
    - "distributed property testing for subgraph freeness revisited"
    - "quadratic and near quadratic lower bounds for the congest model"
    - "on derandomizing local distributed algorithms"
    - "distributed distance bounded network design through distributed convex programming"
    - "near linear lower bounds for distributed distance computations even in sparse networks"
    - "efficient algorithms for constructing very sparse spanners and emulators"

Connected through hyperedge HE-6 (induced by source paper "finding options that minimize planning time"):
  with members:
    - "diversity is all you need learning skills without a reward function"
    - "when waiting is not an option learning options with a deliberation cost"
    - "a laplacian framework for option discovery in reinforcement learning"
    - "constructing abstraction hierarchies using a skill symbol loop"
    - "on the complexity of solving markov decision problems"
    - "analytical approach to parallel repetition"
    - "the complexity of plan existence and evaluation in probabilistic domains"
    - "compositional planning using optimal option models"

Connected through hyperedge HE-7 (induced by source paper "approximating k spanners in the local model"):
  with members:
    - "a fast network decomposition algorithm and its applications to constant time distributed computation"
    - "fault tolerant spanners better and simpler"

Connected through hyperedge HE-8 (induced by source paper "a birthday repetition theorem and complexity of approximating dense csps"):
  with members:
    - "sub exponential approximation schemes for csps from dense to almost sparse"
    - "on the hardness of signaling"
    - "am with multiple merlins"
    - "hypercontractivity sum of squares proofs and their applications"
    - "approximation algorithms and hardness of the k route cut problem"
    - "subsampling mathematical relaxations and average case complexity"

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)