human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "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.

Includes members:
  Member "on problems equivalent to min convolution":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the fine grained complexity of parity problems")
  Member "subquadratic approximation scheme for partition":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "approximating subset sum is equivalent to min plus convolution")
  Member "hardness of approximate nearest neighbor search":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the i o complexity of the k nearest neighbor problem")
  Member "on the hardness of approximate and exact bichromatic maximum inner product":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "approximating subset sum is equivalent to min plus convolution")
  Member "from gap eth to fpt inapproximability clique dominating set and more":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "parameterized inapproximability for steiner orientation by gap amplification")
  Member "on the fine grained complexity of one dimensional dynamic programming":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the fine grained complexity of parity problems")
  Member "distributed pcp theorems for hardness of approximation in p":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "graphs cannot be indexed in polynomial time for sub quadratic time string matching unless seth fails")
  Member "improved rectangular matrix multiplication using powers of the coppersmith winograd tensor":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")

Question: Please tell me which class the source paper 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)