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: "local algorithms for sparse spanning graphs"
  Abstract: We initiate the study of the problem of designing sublinear-time (local) algorithms that, given an edge $(u,v)$ in a connected graph $G=(V,E)$, decide whether $(u,v)$ belongs to a sparse spanning graph $G' = (V,E')$ of $G$. Namely, $G'$ should be connected and $|E'|$ should be upper bounded by $(1+\epsilon)|V|$ for a given parameter $\epsilon > 0$. To this end the algorithms may query the incidence relation of the graph $G$, and we seek algorithms whose query complexity and running time (per given edge $(u,v)$) is as small as possible. Such an algorithm may be randomized but (for a fixed choice of its random coins) its decision on different edges in the graph should be consistent with the same spanning graph $G'$ and independent of the order of queries. #R##N#We first show that for general (bounded-degree) graphs, the query complexity of any such algorithm must be $\Omega(\sqrt{|V|})$. This lower bound holds for graphs that have high expansion. We then turn to design and analyze algorithms both for graphs with high expansion (obtaining a result that roughly matches the lower bound) and for graphs that are (strongly) non-expanding (obtaining results in which the complexity does not depend on $|V|$). The complexity of the problem for graphs that do not fall into these two categories is left as an open question.

Connected through hyperedge HE-1 (induced by source paper "seeing far vs seeing wide volume complexity of local graph problems"):
  with members:
    - "an automatic speedup theorem for distributed problems"
    - "polylogarithmic time deterministic network decomposition and distributed derandomization"
    - "how much does randomness help with locally checkable problems"
    - "locality of not so weak coloring"
    - "almost global problems in the local model"
    - "the distributed complexity of locally checkable problems on paths is decidable"
    - "sparsifying distributed algorithms with ramifications in massively parallel computation and centralized local computation"
    - "hardness of minimal symmetry breaking in distributed computing"

Connected through hyperedge HE-2 (induced by source paper "a local algorithm for the sparse spanning graph problem"):
  with members:
    - "local computation algorithms for graphs of non constant degrees"
    - "a local computation approximation scheme to maximum matching"
    - "a quasi polynomial time partition oracle for graphs with an excluded minor"
    - "converting online algorithms to local computation algorithms"
    - "fast local computation algorithms"
    - "finding cycles and trees in sublinear time"

Connected through hyperedge HE-3 (induced by source paper "sublinear random access generators for preferential attachment graphs"):
  with members:
    - "a scalable generative graph model with community structure"
    - "new techniques and tighter bounds for local computation algorithms"
    - "best of two local models local centralized and local distributed algorithms"
    - "a local computation approximation scheme to maximum matching"
    - "converting online algorithms to local computation algorithms"
    - "space efficient local computation algorithms"
    - "a near optimal sublinear time algorithm for approximating the minimum vertex cover size"
    - "fast local computation algorithms"

Connected through hyperedge HE-4 (induced by source paper "a local algorithm for constructing spanners in minor free graphs"):
  with members:
    - "a local computation approximation scheme to maximum matching"
    - "a quasi polynomial time partition oracle for graphs with an excluded minor"
    - "converting online algorithms to local computation algorithms"
    - "fast local computation algorithms"

Connected through hyperedge HE-5 (induced by source paper "local computation algorithms for graphs of non constant degrees"):
  with members:
    - "flow based algorithms for local graph clustering"
    - "distributed maximum matching in bounded degree graphs"
    - "new techniques and tighter bounds for local computation algorithms"
    - "best of two local models local centralized and local distributed algorithms"
    - "a local computation approximation scheme to maximum matching"
    - "a simple online competitive adaptation of lempel ziv compression with efficient random access support"
    - "local computation mechanism design"
    - "the power of local information in social networks"

Connected through hyperedge HE-6 (induced by source paper "non local probes do not help with graph problems"):
  with members:
    - "distributed maximum matching in bounded degree graphs"
    - "new techniques and tighter bounds for local computation algorithms"
    - "best of two local models local centralized and local distributed algorithms"
    - "large cuts with local algorithms on triangle free graphs"
    - "a local computation approximation scheme to maximum matching"
    - "converting online algorithms to local computation algorithms"
    - "local reconstructors and tolerant testers for connectivity and diameter"
    - "fast local computation algorithms"

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)