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: "semi streaming set cover"
  Abstract: This paper studies the set cover problem under the semi-streaming model. The underlying set system is formalized in terms of a hypergraph $G = (V, E)$ whose edges arrive one-by-one and the goal is to construct an edge cover $F \subseteq E$ with the objective of minimizing the cardinality (or cost in the weighted case) of $F$. We consider a parameterized relaxation of this problem, where given some $0 \leq \epsilon < 1$, the goal is to construct an edge $(1 - \epsilon)$-cover, namely, a subset of edges incident to all but an $\epsilon$-fraction of the vertices (or their benefit in the weighted case). The key limitation imposed on the algorithm is that its space is limited to (poly)logarithmically many bits per vertex. #R##N#Our main result is an asymptotically tight trade-off between $\epsilon$ and the approximation ratio: We design a semi-streaming algorithm that on input graph $G$, constructs a succinct data structure $\mathcal{D}$ such that for every $0 \leq \epsilon   1 / \sqrt{n} \\ O (\sqrt{n}), & \text{otherwise} \end{array} \right. \, . \] In particular for the traditional set cover problem we obtain an $O(\sqrt{n})$-approximation. This algorithm is proved to be best possible by establishing a family (parameterized by $\epsilon$) of matching lower bounds.

Connected through hyperedge HE-1 (induced by source paper "polynomial pass lower bounds for graph streaming algorithms"):
  with members:
    - "smaller cuts higher lower bounds"
    - "parallelization does not accelerate convex optimization adaptivity lower bounds for non smooth convex minimization"
    - "an exponential speedup in parallel running time for submodular maximization without loss in approximation"
    - "non monotone submodular maximization with nearly optimal adaptivity complexity"
    - "submodular maximization with optimal approximation adaptivity and query complexity"
    - "tight bounds on the round complexity of the distributed maximum coverage problem"
    - "non monotone submodular maximization in exponentially fewer iterations"
    - "submodular maximization with nearly optimal approximation and adaptivity in nearly linear time"

Connected through hyperedge HE-2 (induced by source paper "approximate mathbb f _2 sketching of valuation functions"):
  with members:
    - "optimality of linear sketching under modular updates"
    - "optimal lower bounds for universal relation and for samplers and finding duplicates in streams"
    - "testing submodularity and other properties of valuation functions"
    - "almost optimal streaming algorithms for coverage problems"
    - "tight bounds for single pass streaming complexity of the set cover problem"
    - "towards tight bounds for the streaming set cover problem"
    - "streaming algorithms for submodular function maximization"
    - "incidence geometries and the pass complexity of semi streaming set cover"

Connected through hyperedge HE-3 (induced by source paper "improved local computation algorithm for set cover via sparsification"):
  with members:
    - "sparsifying distributed algorithms with ramifications in massively parallel computation and centralized local computation"
    - "round compression for parallel graph algorithms in strongly sublinear space"
    - "tight space approximation tradeoff for the multi pass streaming set cover problem"
    - "almost optimal streaming algorithms for coverage problems"
    - "tight bounds for single pass streaming complexity of the set cover problem"
    - "towards tight bounds for the streaming set cover problem"
    - "incidence geometries and the pass complexity of semi streaming set cover"
    - "a nearly linear time ptas for explicit fractional packing and covering linear programs"

Connected through hyperedge HE-4 (induced by source paper "streaming frequent items with timestamps and detecting large neighborhoods in graph streams"):
  with members:
    - "optimality of linear sketching under modular updates"
    - "independent sets in vertex arrival streams"
    - "tight space approximation tradeoff for the multi pass streaming set cover problem"
    - "tight bounds for single pass streaming complexity of the set cover problem"
    - "towards tight bounds for the streaming set cover problem"
    - "maximum matching in turnstile streams"
    - "tight bounds for lp samplers finding duplicates in streams and related problems"
    - "analysis of a bloom filter algorithm via the supermarket model"

Connected through hyperedge HE-5 (induced by source paper "tight bounds on the round complexity of the distributed maximum coverage problem"):
  with members:
    - "distributed partial clustering"
    - "tight space approximation tradeoff for the multi pass streaming set cover problem"
    - "on estimating maximum matching size in graph streams"
    - "combinatorial auctions do need modest interaction"
    - "submodular optimization over sliding windows"
    - "distributed coverage maximization via sketching"
    - "almost optimal streaming algorithms for coverage problems"
    - "better streaming algorithms for the maximum coverage problem"

Connected through hyperedge HE-6 (induced by source paper "set cover and vertex cover with delay"):
  with members:
    - "a primal dual online deterministic algorithm for matching with delays"
    - "deterministic min cost matching with delays"
    - "online service with delay"
    - "a match in time saves nine deterministic online matching with delays"
    - "online and dynamic algorithms for set cover"
    - "online matching haste makes waste"
    - "the online disjoint set cover problem and its applications"
    - "minimum latency submodular cover"

Connected through hyperedge HE-7 (induced by source paper "tight space approximation tradeoff for the multi pass streaming set cover problem"):
  with members:
    - "submodular optimization over sliding windows"
    - "almost optimal streaming algorithms for coverage problems"
    - "better streaming algorithms for the maximum coverage problem"
    - "submodular maximization over sliding windows"
    - "tight bounds for single pass streaming complexity of the set cover problem"
    - "towards tight bounds for the streaming set cover problem"
    - "incidence geometries and the pass complexity of semi streaming set cover"
    - "analytical approach to parallel repetition"

Connected through hyperedge HE-8 (induced by source paper "almost optimal streaming algorithms for coverage problems"):
  with members:
    - "submodular optimization under noise"
    - "distributed coverage maximization via sketching"
    - "better streaming algorithms for the maximum coverage problem"
    - "tight bounds for single pass streaming complexity of the set cover problem"
    - "towards tight bounds for the streaming set cover problem"
    - "kernelization via sampling with applications to dynamic graph streams"
    - "tight bounds for linear sketches of approximate matchings"
    - "randomized composable core sets for distributed submodular maximization"

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)