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 the fine grained complexity of parity problems"):
  Abstract: We consider the parity variants of basic problems studied in fine-grained complexity. We show that finding the exact solution is just as hard as finding its parity (i.e. if the solution is even or odd) for a large number of classical problems, including All-Pairs Shortest Paths (APSP), Diameter, Radius, Median, Second Shortest Path, Maximum Consecutive Subsums, Min-Plus Convolution, and $0/1$-Knapsack. #R##N#A direct reduction from a problem to its parity version is often difficult to design. Instead, we revisit the existing hardness reductions and tailor them in a problem-specific way to the parity version. Nearly all reductions from APSP in the literature proceed via the (subcubic-equivalent but simpler) Negative Weight Triangle (NWT) problem. Our new modified reductions also start from NWT or a non-standard parity variant of it. We are not able to establish a subcubic-equivalence with the more natural parity counting variant of NWT, where we ask if the number of negative triangles is even or odd. Perhaps surprisingly, we justify this by designing a reduction from the seemingly-harder Zero Weight Triangle problem, showing that parity is (conditionally) strictly harder than decision for NWT.

Includes members:
  Member "subcubic equivalences between graph centrality measures and complementary problems":
    also connected through other hyperedges:
      (none)
  Member "approximating subset sum is equivalent to min plus convolution":
    also connected through other hyperedges:
      (none)
  Member "on problems equivalent to min convolution":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "faster minimization of tardy processing newline time on a single machine")
  Member "a subquadratic algorithm for 3xor":
    also connected through other hyperedges:
      (none)
  Member "fine grained reductions from approximate counting to decision":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "approximately counting and sampling small witnesses using a colourful decision oracle")
  Member "fine grained i o complexity via reductions new lower bounds faster algorithms and a time hierarchy":
    also connected through other hyperedges:
      - Hyperedge HE-3 (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-4 (induced by source paper "approximating subset sum is equivalent to min plus convolution")
  Member "tight hardness results for maximum weight rectangles":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "truly subcubic min plus product for less structured matrices with applications")

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)