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: "tree edit distance cannot be computed in strongly subcubic time unless apsp can"
  Abstract: The edit distance between two rooted ordered trees with $n$ nodes labeled from an alphabet~$\Sigma$ is the minimum cost of transforming one tree into the other by a sequence of elementary operations consisting of deleting and relabeling existing nodes, as well as inserting new nodes. Tree edit distance is a well known generalization of string edit distance. The fastest known algorithm for tree edit distance runs in cubic $O(n^3)$ time and is based on a similar dynamic programming solution as string edit distance. In this paper we show that a truly subcubic $O(n^{3-\varepsilon})$ time algorithm for tree edit distance is unlikely: For $|\Sigma| = \Omega(n)$, a truly subcubic algorithm for tree edit distance implies a truly subcubic algorithm for the all pairs shortest paths problem. For $|\Sigma| = O(1)$, a truly subcubic algorithm for tree edit distance implies an $O(n^{k-\varepsilon})$ algorithm for finding a maximum weight $k$-clique. #R##N#Thus, while in terms of upper bounds string edit distance and tree edit distance are highly related, in terms of lower bounds string edit distance exhibits the hardness of the strong exponential time hypothesis [Backurs, Indyk STOC'15] whereas tree edit distance exhibits the hardness of all pairs shortest paths. Our result provides a matching conditional lower bound for one of the last remaining classic dynamic programming problems.

Connected through hyperedge HE-1 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs"):
  with members:
    - "decremental sssp in weighted digraphs faster and against an adaptive adversary"
    - "fully dynamic all pairs shortest paths improved worst case time and space bounds"
    - "deterministic algorithms for decremental approximate shortest paths faster and simpler"
    - "decremental strongly connected components and single source reachability in near linear time"
    - "graph pattern detection hardness for all induced patterns and faster non induced cycles"
    - "limits on all known and some unknown approaches to matrix multiplication"
    - "diameter spanners eccentricity spanners and approximating extremal distances"
    - "limits on the universal method for matrix multiplication"

Connected through hyperedge HE-2 (induced by source paper "the geometry of syntax and semantics for directed file transformations"):
  with members:
    - "dire a neural approach to decompiled identifier naming"
    - "synthesizing bijective lenses"
    - "a language theoretic view on network protocols"
    - "de bruijn entropy and string similarity"
    - "an optimal decomposition algorithm for tree edit distance"

Connected through hyperedge HE-3 (induced by source paper "subcubic equivalences between graph centrality measures and complementary problems"):
  with members:
    - "tight hardness for shortest cycles and paths in sparse graphs"
    - "if the current clique algorithms are optimal so is valiant s parser"
    - "popular conjectures imply strong lower bounds for dynamic problems"
    - "edit distance cannot be computed in strongly subquadratic time unless seth is false"
    - "faster all pairs shortest paths via circuit complexity"
    - "all pairs shortest paths using bridging sets and rectangular matrix multiplication"

Connected through hyperedge HE-4 (induced by source paper "more consequences of falsifying seth and the orthogonal vectors conjecture"):
  with members:
    - "on the fine grained complexity of empirical risk minimization kernel methods and neural networks"
    - "conditional lower bounds for all pairs max flow"
    - "on the fine grained complexity of one dimensional dynamic programming"
    - "distributed pcp theorems for hardness of approximation in p"
    - "fine grained complexity of analyzing compressed data quantifying improvements over decompress and solve"
    - "improving viterbi is hard better runtimes imply faster clique algorithms"
    - "on the hardness of partially dynamic graph problems and connections to diameter"
    - "tight hardness results for maximum weight rectangles"

Connected through hyperedge HE-5 (induced by source paper "voronoi diagrams on planar graphs and computing the diameter in deterministic tilde o n 5 3 time"):
  with members:
    - "fast and compact exact distance oracle for planar graphs"
    - "subquadratic algorithms for the diameter and the sum of pairwise distances in planar graphs"
    - "improving viterbi is hard better runtimes imply faster clique algorithms"
    - "popular conjectures as a barrier for dynamic planar graph algorithms"
    - "optimal parameterized algorithms for planar facility location problems using voronoi diagrams"
    - "popular conjectures imply strong lower bounds for dynamic problems"
    - "exact weight subgraphs and the k sum conjecture"
    - "faster all pairs shortest paths via circuit complexity"

Connected through hyperedge HE-6 (induced by source paper "tight hardness for shortest cycles and paths in sparse graphs"):
  with members:
    - "finding even cycles faster via capped k walks"
    - "fine grained complexity and conditional hardness for sparse graphs"
    - "polynomial representations of threshold functions and algorithmic applications"
    - "the input output complexity of triangle enumeration"
    - "powers of tensors and fast matrix multiplication"
    - "faster all pairs shortest paths via circuit complexity"
    - "algorithmic applications of baur strassen s theorem shortest cycles diameter and matchings"
    - "all pairs shortest paths using bridging sets and rectangular matrix multiplication"

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)