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 "greed is not always good on submodular maximization over independence systems"):
  Abstract: In this work, we consider the maximization of submodular functions constrained by independence systems. Because of the wide applicability of submodular functions, this problem has been extensively studied in the literature. When the independence system is a $p$-system, prior literature has claimed that the greedy algorithm achieves a $1/(p+1)$-approximation if the submodular function is monotone. We show that, on the contrary, for any $\epsilon > 0$, the problem is hard to approximate within $(2/n)^{1-\epsilon}$, where $n$ is the size of the ground set, even when the independence system is a $1$-system. This result invalidates prior work on constant-factor algorithms for non-monotone submodular maximization over $p$-systems as well. On the positive side, we provide the first nearly linear-time algorithm for maximization of non-monotone submodular functions over $p$-extendible independence systems, which are a subclass of $p$-systems.

Includes members:
  Member "streaming non monotone submodular maximization personalized video summarization on the fly":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimal streaming algorithms for submodular maximization with cardinality constraints")
  Member "greed is good near optimal submodular maximization via greedy optimization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "regularized submodular maximization at scale")

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)