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: "superlinear lower bounds for multipass graph processing"
  Abstract: We prove $n^{1+\Omega(1/p)}/p^{O(1)}$ lower bounds for the space complexity of $p$-pass streaming algorithms solving the following problems on $n$-vertex graphs: #R##N#* testing if an undirected graph has a perfect matching (this implies lower bounds for computing a maximum matching or even just the maximum matching size), #R##N#* testing if two specific vertices are at distance at most $2(p+1)$ in an undirected graph, #R##N#* testing if there is a directed path from $s$ to $t$ for two specific vertices $s$ and $t$ in a directed graph. #R##N#Prior to our result, it was known that these problems require $\Omega(n^2)$ space in one pass, but no $n^{1+\Omega(1)}$ lower bound was known for any $p\ge 2$. #R##N#These streaming results follow from a communication complexity lower bound for a communication game in which the players hold two graphs on the same set of vertices. The task of the players is to find out whether the sets of vertices at distance exactly $p+1$ from a specific vertex intersect. The game requires a significant amount of communication only if the players are forced to speak in a specific difficult order. This is reminiscent of lower bounds for communication problems such as indexing and pointer chasing. Among other things, our line of attack requires proving an information cost lower bound for a decision version of the classic pointer chasing problem and a direct sum type theorem for the disjunction of several instances of this problem.

Connected through hyperedge HE-1 (induced by source paper "two player hidden pointer chasing and multi pass lower bounds in turnstile streams"):
  with members:
    - "approximate maximum matching in random streams"
    - "polynomial pass lower bounds for graph streaming algorithms"
    - "dynamic streaming spectral sparsification in nearly linear time and space"
    - "weighted matchings via unweighted augmentations"
    - "tight bounds on the round complexity of the distributed maximum coverage problem"
    - "tight space approximation tradeoff for the multi pass streaming set cover problem"
    - "simplified and space optimal semi streaming for 2 epsilon approximate matching"
    - "on estimating maximum matching size in graph streams"

Connected through hyperedge HE-2 (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-3 (induced by source paper "depth first search in the semi streaming model"):
  with members:
    - "incremental dfs algorithms a theoretical and experimental study"
    - "distributed exact shortest paths in sublinear time"
    - "near optimal parallel algorithms for dynamic dfs in undirected graphs"
    - "dynamic dfs in undirected graphs breaking the o m barrier"
    - "real time monitoring of undirected networks articulation points bridges and connected and biconnected components"
    - "better bounds for matchings in the streaming model"
    - "defining and evaluating network communities based on ground truth"
    - "linear programming in the semi streaming model with application to the maximum matching problem"

Connected through hyperedge HE-4 (induced by source paper "the sketching complexity of graph and hypergraph counting"):
  with members:
    - "size bounds and query plans for relational joins"
    - "estimating graph parameters from random order streams"
    - "on estimating maximum matching size in graph streams"
    - "on the multiparty communication complexity of testing triangle freeness"
    - "escape efficiently counting all 5 vertex subgraphs"
    - "on approximating functions of the singular values in a stream"
    - "kernelization via sampling with applications to dynamic graph streams"
    - "tight bounds for linear sketches of approximate matchings"

Connected through hyperedge HE-5 (induced by source paper "an optimal space lower bound for approximating max cut"):
  with members:
    - "the sketching complexity of graph and hypergraph counting"
    - "estimating graph parameters from random order streams"
    - "on estimating maximum matching size in graph streams"
    - "sublinear estimation of weighted matchings in dynamic data streams"
    - "maximum matching in turnstile streams"
    - "sketching cuts in graphs and hypergraphs"
    - "streaming lower bounds for approximating max cut"
    - "single pass spectral sparsification in dynamic streams"

Connected through hyperedge HE-6 (induced by source paper "on estimating maximum matching size in graph streams"):
  with members:
    - "on approximating functions of the singular values in a stream"
    - "sublinear estimation of weighted matchings in dynamic data streams"
    - "maximum matching in turnstile streams"
    - "on the communication complexity of linear algebraic problems in the message passing model"
    - "access to data and number of iterations dual primal algorithms for maximum matching under resource constraints"
    - "better bounds for matchings in the streaming model"
    - "maximum matching in semi streaming with few passes"
    - "improved approximation guarantees for weighted matching in the semi streaming model"

Connected through hyperedge HE-7 (induced by source paper "distributed exact shortest paths in sublinear time"):
  with members:
    - "approximate undirected transshipment and shortest paths via gradient descent"
    - "efficient algorithms for constructing very sparse spanners and emulators"
    - "hopsets with constant hopbound and applications to approximate shortest paths"
    - "algebraic methods in the congested clique"
    - "a deterministic almost tight distributed algorithm for approximating single source shortest paths"
    - "approximation of distances and shortest paths in the broadcast congest clique"
    - "almost tight distributed minimum cut algorithms"
    - "distributed approximation algorithms for weighted shortest paths"

Connected through hyperedge HE-8 (induced by source paper "near optimal approximate shortest paths and transshipment in distributed and streaming models"):
  with members:
    - "thorup zwick emulators are universally optimal hopsets"
    - "distributed exact shortest paths in sublinear time"
    - "improved distributed algorithms for exact shortest paths"
    - "further algebraic algorithms in the congested clique model and applications to graph theoretic problems"
    - "generalized preconditioning and network flow problems"
    - "parallel shortest paths using radius stepping"
    - "a hierarchy of lower bounds for sublinear additive spanners"
    - "hopsets with constant hopbound and applications to approximate shortest paths"

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.CC(Computational Complexity)