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: "converting online algorithms to local computation algorithms"
  Abstract: We propose a general method for converting online algorithms to local computation algorithms by selecting a random permutation of the input, and simulating running the online algorithm. We bound the number of steps of the algorithm using a query tree, which models the dependencies between queries. We improve previous analyses of query trees on graphs of bounded degree, and extend the analysis to the cases where the degrees are distributed binomially, and to a special case of bipartite graphs. #R##N#Using this method, we give a local computation algorithm for maximal matching in graphs of bounded degree, which runs in time and space O(log^3 n). #R##N#We also show how to convert a large family of load balancing algorithms (related to balls and bins problems) to local computation algorithms. This gives several local load balancing algorithms which achieve the same approximation ratios as the online algorithms, but run in O(log n) time and space. #R##N#Finally, we modify existing local computation algorithms for hypergraph 2-coloring and k-CNF and use our improved analysis to obtain better time and space bounds, of O(log^4 n), removing the dependency on the maximal degree of the graph from the exponent.

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 "space efficient approximation to maximum matching size from uniform edge samples"):
  with members:
    - "sparsifying distributed algorithms with ramifications in massively parallel computation and centralized local computation"
    - "weighted matchings via unweighted augmentations"
    - "coresets meet edcs algorithms for matching and vertex cover on massive graphs"
    - "extractor based time space lower bounds for learning"
    - "estimating graph parameters from random order streams"
    - "testable bounded degree graph properties are random order streamable"
    - "on estimating maximum matching size in graph streams"
    - "a 2 ϵ approximation for maximum weight matching in the semi streaming model"

Connected through hyperedge HE-3 (induced by source paper "robust clustering oracle and local reconstructor of cluster structure of graphs"):
  with members:
    - "testing graph clusterability algorithms and lower bounds"
    - "approximate correlation clustering using same cluster queries"
    - "approximate clustering with same cluster queries"
    - "clustering with same cluster queries"
    - "learning communities in the presence of errors"
    - "testing cluster structure of graphs"
    - "how robust are reconstruction thresholds for community detection"
    - "correlation clustering with noisy partial information"

Connected through hyperedge HE-4 (induced by source paper "a local algorithm for the sparse spanning graph problem"):
  with members:
    - "local computation algorithms for graphs of non constant degrees"
    - "local algorithms for sparse spanning graphs"
    - "a local computation approximation scheme to maximum matching"
    - "a quasi polynomial time partition oracle for graphs with an excluded minor"
    - "fast local computation algorithms"
    - "finding cycles and trees in sublinear time"

Connected through hyperedge HE-5 (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"
    - "local algorithms for sparse spanning graphs"
    - "a local computation approximation scheme to maximum matching"
    - "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-6 (induced by source paper "a local algorithm for constructing spanners in minor free graphs"):
  with members:
    - "local algorithms for sparse spanning graphs"
    - "a local computation approximation scheme to maximum matching"
    - "a quasi polynomial time partition oracle for graphs with an excluded minor"
    - "fast local computation algorithms"

Connected through hyperedge HE-7 (induced by source paper "on giant components and treewidth in the layers model"):
  with members:
    - "recoverable values for independent sets"

Connected through hyperedge HE-8 (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"
    - "local algorithms for sparse spanning graphs"
    - "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"

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)