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 "on problems equivalent to min convolution"):
  Abstract: In recent years, significant progress has been made in explaining the apparent hardness of improving upon the naive solutions for many fundamental polynomially solvable problems. This progress has come in the form of conditional lower bounds—reductions from a problem assumed to be hard. The hard problems include 3SUM, All-Pairs Shortest Path, SAT, Orthogonal Vectors, and others.#R##N##R##N#In the (min ,+)-convolution problem, the goal is to compute a sequence (c[i])n-1i=0, where c[k] = mini=0,…; ,k { a[i] + b[k-i]}, given sequences (a[i])n-1i=0 and (b[i])n-1i=0. This can easily be done in O(n2) time, but no O(n2-e) algorithm is known for e > 0. In this article, we undertake a systematic study of the (min ,+)-convolution problem as a hardness assumption.#R##N##R##N#First, we establish the equivalence of this problem to a group of other problems, including variants of the classic knapsack problem and problems related to subadditive sequences. The (min ,+)-convolution problem has been used as a building block in algorithms for many problems, notably problems in stringology. It has also appeared as an ad hoc hardness assumption. Second, we investigate some of these connections and provide new reductions and other results. We also explain why replacing this assumption with the Strong Exponential Time Hypothesis might not be possible for some problems.

Includes members:
  Member "how hard is it to find honest witnesses":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "all non trivial variants of 3 ldt are equivalent")
  Member "seth based lower bounds for subset sum and bicriteria path":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "scheduling lower bounds via and subset sum")
  Member "on the fine grained complexity of one dimensional dynamic programming":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the fine grained complexity of parity problems")
  Member "on problems as hard as cnf sat":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "a near linear pseudopolynomial time algorithm for subset sum":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "scheduling lower bounds via and subset sum")
  Member "clustered integer 3sum via additive combinatorics":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "all non trivial variants of 3 ldt are equivalent")
  Member "a faster fptas for the unbounded knapsack problem":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an improved fptas for 0 1 knapsack")
  Member "a faster pseudopolynomial time algorithm for subset sum":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "scheduling lower bounds via and subset sum")

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)