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: "tight bounds for single pass streaming complexity of the set cover problem"
  Abstract: We resolve the space complexity of single-pass streaming algorithms for approximating the classic set cover problem. For finding an $\alpha$-approximate set cover (for any $\alpha= o(\sqrt{n})$) using a single-pass streaming algorithm, we show that $\Theta(mn/\alpha)$ space is both sufficient and necessary (up to an $O(\log{n})$ factor); here $m$ denotes number of the sets and $n$ denotes size of the universe. This provides a strong negative answer to the open question posed by Indyk et al. (2015) regarding the possibility of having a single-pass algorithm with a small approximation factor that uses sub-linear space. #R##N#We further study the problem of estimating the size of a minimum set cover (as opposed to finding the actual sets), and establish that an additional factor of $\alpha$ saving in the space is achievable in this case and that this is the best possible. In other words, we show that $\Theta(mn/\alpha^2)$ space is both sufficient and necessary (up to logarithmic factors) for estimating the size of a minimum set cover to within a factor of $\alpha$. Our algorithm in fact works for the more general problem of estimating the optimal value of a covering integer program. On the other hand, our lower bound holds even for set cover instances where the sets are presented in a random order.

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"
    - "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"
    - "tight bounds on low degree spectral concentration of submodular and xos functions"

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"
    - "towards tight bounds for the streaming set cover problem"
    - "incidence geometries and the pass complexity of semi streaming set cover"
    - "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"
    - "towards tight bounds for the streaming set cover problem"
    - "maximum matching in turnstile streams"
    - "semi streaming set cover"
    - "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 "set cover in sub linear time"):
  with members:
    - "almost optimal streaming algorithms for coverage problems"
    - "towards tight bounds for the streaming set cover problem"
    - "randomized composable core sets for distributed submodular maximization"
    - "incidence geometries and the pass complexity of semi streaming set cover"
    - "a nearly linear time ptas for explicit fractional packing and covering linear programs"
    - "analytical approach to parallel repetition"
    - "a near optimal sublinear time algorithm for approximating the minimum vertex cover size"

Connected through hyperedge HE-6 (induced by source paper "structural parameterization for graph deletion problems over data streams"):
  with members:
    - "on the streaming complexity of fundamental geometric problems"
    - "faster deterministic feedback vertex set"
    - "interval deletion is fixed parameter tractable"
    - "linear kernels and single exponential algorithms via protrusion decompositions"
    - "preprocessing subgraph and minor problems when does a small vertex cover help"
    - "hitting forbidden minors approximation and kernelization"

Connected through hyperedge HE-7 (induced by source paper "distributed and streaming linear programming in low dimensions"):
  with members:
    - "communication steps for parallel query processing"
    - "efficient protocols for distributed classification and optimization"
    - "sorting searching and simulation in the mapreduce framework"
    - "lower bounds for number in hand multiparty communication complexity made easy"
    - "linear programming in the semi streaming model with application to the maximum matching problem"
    - "lower bounds for predecessor searching in the cell probe model"

Connected through hyperedge HE-8 (induced by source paper "towards a theory of parameterized streaming algorithms"):
  with members:
    - "towards tight er bounds for the excluded grid theorem"
    - "the sparse awakens streaming algorithms for matching size estimation in sparse graphs"
    - "towards tight bounds for the streaming set cover problem"
    - "polynomial bounds for the grid minor theorem"
    - "directed subset feedback vertex set is fixed parameter tractable"

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)