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 "a new approximation guarantee for monotone submodular function maximization via discrete convexity"):
  Abstract: In monotone submodular function maximization, approximation guarantees based on the curvature of the objective function have been extensively studied in the literature. However, the notion of curvature is often pessimistic, and we rarely obtain improved approximation guarantees, even for very simple objective functions. #R##N#In this paper, we provide a novel approximation guarantee by extracting an M$^\natural$-concave function $h:2^E \to \mathbb R_+$, a notion in discrete convex analysis, from the objective function $f:2^E \to \mathbb R_+$. We introduce the notion of $h$-curvature, which measures how much $f$ deviates from $h$, and show that we can obtain a $(1-\gamma/e-\epsilon)$-approximation to the problem of maximizing $f$ under a cardinality constraint in polynomial time for any constant $\epsilon > 0$. Then, we show that we can obtain nontrivial approximation guarantees for various problems by applying the proposed algorithm.

Includes members:
  Member "stability and recovery for independence systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the unreasonable effectiveness of the greedy algorithm greedy adapts to sharpness")
  Member "maximizing a monotone submodular function with a bounded curvature under a knapsack constraint":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "approximability of monotone submodular function maximization under cardinality and matroid constraints in the streaming model")
  Member "submodular optimization with submodular cover and submodular knapsack constraints":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "robust submodular minimization with applications to cooperative modeling")
  Member "optimal approximation for submodular and supermodular optimization with bounded curvature":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "regularized submodular maximization at scale")
  Member "learning mixtures of submodular shells with application to document summarization":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "robust submodular minimization with applications to cooperative modeling")
  Member "submodular function maximization via the multilinear relaxation and contention resolution schemes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "approximability of monotone submodular function maximization under cardinality and matroid constraints in the streaming model")
  Member "combinatorial auctions with decreasing marginal utilities":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "complexity theory game theory and economics the barbados lectures")

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)