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 maximization using test scores"):
  Abstract: We consider the closely related problems of maximizing a submodular function subject to a cardinality constraint and that of maximizing the sum of submodular functions subject to a partition matroid contraint. Motivated by applications in team selection, we focus on settings where the function(s) can be expressed as the expected value of a symmetric submodular value function of a set of independent random variables with given prior distributions, and where, the algorithm designer may not be able to access the submodular function by means of value oracle queries. We consider a novel approach towards submodular maximization known as test score algorithms whose functioning is restricted to computing a test score for each element of the ground set and using these test scores to estimate the outputs of oracle calls. Our main contributions are test score algorithms that yield constant factor and logarithmic approximations respectively for the two problems along with new insights pertaining to function sketching. We also identify necessary and sufficient conditions under which test score algorithms provide constant-factor approximations for the submodular maximization problem. We evaluate the quality of our algorithms for team selection using data from a popular online labour platform for software development.

Includes members:
  Member "submodular optimization under noise":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "searching trees with permanently noisy advice walking and query algorithms")
  Member "noisy submodular maximization via adaptive sampling with applications to crowdsourced image collection summarization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimal approximation for unconstrained non submodular minimization")
  Member "team performance with test scores":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "sketching with test scores and submodular maximization")
  Member "faster and simpler sketches of valuation functions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "sketching with test scores and submodular maximization")
  Member "submodular optimization with submodular cover and submodular knapsack constraints":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "robust submodular minimization with applications to cooperative modeling")
  Member "optimal bounds on approximation of submodular and xos functions by juntas":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "approximate mathbb f _2 sketching of valuation functions")
  Member "optimal approximation for submodular and supermodular optimization with bounded curvature":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "regularized submodular maximization at scale")
  Member "combinatorial auctions with decreasing marginal utilities":
    also connected through other hyperedges:
      - Hyperedge HE-8 (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)