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 "submodular cost submodular cover with an approximate oracle"):
  Abstract: In this work, we study the Submodular Cost Submodular Cover problem, which is to minimize the submodular cost required to ensure that the submodular benefit function exceeds a given threshold. Existing approximation ratios for the greedy algorithm assume a value oracle to the benefit function. However, access to a value oracle is not a realistic assumption for many applications of this problem, where the benefit function is difficult to compute. We present two incomparable approximation ratios for this problem with an approximate value oracle and demonstrate that the ratios take on empirically relevant values through a case study with the Influence Threshold problem in online social networks.

Includes members:
  Member "weakly submodular maximization beyond cardinality constraints does randomization help greedy":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "black box submodular maximization discrete and continuous settings")
  Member "cost effective seed selection in online social networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "efficient approximation algorithms for adaptive seed minimization")
  Member "why approximate when you can get the exact optimal targeted viral marketing at scale":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "importance sample based approximation algorithm for cost aware targeted viral marketing")
  Member "guarantees for greedy maximization of non submodular functions with applications":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "optimal approximation for unconstrained non submodular minimization")
  Member "scalable bicriteria algorithms for the threshold activation problem in online social networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "an efficient evolutionary algorithm for minimum cost submodular cover")
  Member "submodular optimization under noise":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "searching trees with permanently noisy advice walking and query algorithms")
  Member "an efficient streaming algorithm for the submodular cover problem":
    also connected through other hyperedges:
      (none)
  Member "noisy submodular maximization via adaptive sampling with applications to crowdsourced image collection summarization":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "optimal approximation for unconstrained non submodular minimization")

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)