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: "approximating apsp without scaling equivalence of approximate min plus and exact min max"
  Abstract: Zwick’s (1+e)-approximation algorithm for the All Pairs Shortest Path (APSP) problem runs in time O(nω/e logW), where ω ≤ 2.373 is the exponent of matrix multiplication and W denotes the largest weight. This can be used to approximate several graph characteristics including the diameter, radius, median, minimum-weight triangle, and minimum-weight cycle in the same time bound.    Since Zwick’s algorithm uses the scaling technique, it has a factor logW in the running time. In this paper, we study whether APSP and related problems admit approximation schemes avoiding the scaling technique. That is, the number of arithmetic operations should be independent of W; this is called strongly polynomial. Our main results are as follows.    (1) We design approximation schemes in strongly polynomial time O(nω/e polylog(n/e)) for APSP on undirected graphs as well as for the graph characteristics diameter, radius, median, minimum-weight triangle, and minimum-weight cycle on directed or undirected graphs.    (2) For APSP on directed graphs we design an approximation scheme in strongly polynomial time O(nω + 3/2 e−1 polylog(n/e)). This is significantly faster than the best exact algorithm.    (3) We explain why our approximation scheme for APSP on directed graphs has a worse exponent than ω: Any improvement over our exponent ω + 3/2 would improve the best known algorithm for Min-Max Product. In fact, we prove that approximating directed APSP and exactly computing the Min-Max Product are equivalent.    Our techniques yield a framework for approximation problems over the (min,+)-semiring that can be applied more generally. In particular, we obtain the first strongly polynomial approximation scheme for Min-Plus Convolution in strongly subquadratic time, and we prove an equivalence of approximate Min-Plus Convolution and exact Min-Max Convolution.

Connected through hyperedge HE-1 (induced by source paper "shortest path centrality and the all pairs shortest paths problem via vc dimension theory"):
  with members:
    - "estimating the percolation centrality of large networks through pseudo dimension theory"
    - "almost shortest paths and pram distance oracles in weighted graphs"
    - "abra approximating betweenness centrality in static and dynamic graphs with rademacher averages"
    - "on the shoshan zwick algorithm for the all pairs shortest path problem"
    - "popular conjectures imply strong lower bounds for dynamic problems"
    - "faster all pairs shortest paths via circuit complexity"
    - "shape fitting on point sets with probability distributions"

Connected through hyperedge HE-2 (induced by source paper "approximating subset sum is equivalent to min plus convolution"):
  with members:
    - "an improved fptas for 0 1 knapsack"
    - "on problems equivalent to min convolution"
    - "subquadratic approximation scheme for partition"
    - "fast algorithms for knapsack via convolution and prediction"
    - "an equivalence class for orthogonal vectors"
    - "on integer programming and convolution"
    - "on the hardness of approximate and exact bichromatic maximum inner product"
    - "a simple near linear pseudopolynomial time randomized algorithm for subset sum"

Connected through hyperedge HE-3 (induced by source paper "equivalences between triangle and range query problems"):
  with members:
    - "computing quartet distance is equivalent to counting 4 cycles"
    - "algorithms and hardness for diameter in dynamic graphs"
    - "tight hardness for shortest cycles and paths in sparse graphs"
    - "improved rectangular matrix multiplication using powers of the coppersmith winograd tensor"
    - "powers of tensors and fast matrix multiplication"
    - "popular conjectures imply strong lower bounds for dynamic problems"
    - "higher lower bounds from the 3sum conjecture"
    - "minimum weight cycles and triangles equivalences and algorithms"

Connected through hyperedge HE-4 (induced by source paper "1 0 1 apsp and min max product problems"):
  with members:
    - "improved rectangular matrix multiplication using powers of the coppersmith winograd tensor"
    - "powers of tensors and fast matrix multiplication"
    - "faster all pairs shortest paths via circuit complexity"

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)