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 "scheduling lower bounds via and subset sum"):
  Abstract: Given $N$ instances $(X_1,t_1),\ldots,(X_N,t_N)$ of Subset Sum, the AND Subset Sum problem asks to determine whether all of these instances are yes-instances; that is, whether each set of integers $X_i$ has a subset that sums up to the target integer $t_i$. We prove that this problem cannot be solved in $\tilde{O}((N \cdot t_{max})^{1-\epsilon})$ time, for $t_{max}=\max_i t_i$ and any $\epsilon > 0$, assuming the $\forall \exists$ Strong Exponential Time Hypothesis ($\forall \exists$-SETH). We then use this result to exclude $\tilde{O}(n+P_{max} \cdot n^{1-\epsilon})$-time algorithms for several scheduling problems on $n$ jobs with maximum processing time $P_{max}$, based on $\forall \exists$-SETH. These include classical problems such as $1||\sum w_jU_j$, the problem of minimizing the total weight of tardy jobs on a single machine, and $P_2||\sum U_j$, the problem of minimizing the number of tardy jobs on two identical parallel machines.

Includes members:
  Member "conditional hardness of earth mover distance":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a data dependent algorithm for querying earth mover s distance with low doubling dimension")
  Member "polyline simplification has cubic complexity":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "global curve simplification")
  Member "a simple near linear pseudopolynomial time randomized algorithm for subset sum":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "approximating subset sum is equivalent to min plus convolution")
  Member "fast modular subset sum using linear sketching":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "approximating subset sum is equivalent to min plus convolution")
  Member "algorithms and hardness for diameter in dynamic graphs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")
  Member "seth based lower bounds for subset sum and bicriteria path":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "faster minimization of tardy processing newline time on a single machine")
  Member "fine grained i o complexity via reductions new lower bounds faster algorithms and a time hierarchy":
    also connected through other hyperedges:
      - Hyperedge HE-7 (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-8 (induced by source paper "coarse grained complexity for dynamic algorithms")

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)