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 "the complexity of partial function extension for coverage functions"):
  Abstract: Coverage functions are an important subclass of submodular functions, finding applications in machine learning, game theory, social networks, and facility location. We study the complexity of partial function extension to coverage functions. That is, given a partial function consisting of a family of subsets of $[m]$ and a value at each point, does there exist a coverage function defined on all subsets of $[m]$ that extends this partial function? Partial function extension is previously studied for other function classes, including boolean functions and convex functions, and is useful in many fields, such as obtaining bounds on learning these function classes. #R##N#We show that determining extendibility of a partial function to a coverage function is NP-complete, establishing in the process that there is a polynomial-sized certificate of extendibility. The hardness also gives us a lower bound for learning coverage functions. We then study two natural notions of approximate extension, to account for errors in the data set. The two notions correspond roughly to multiplicative point-wise approximation and additive $L_1$ approximation. We show upper and lower bounds for both notions of approximation. In the second case we obtain nearly tight bounds.

Includes members:
  Member "partial function extension with applications to learning and property testing":
    also connected through other hyperedges:
      (none)
  Member "the limitations of optimization from samples":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "polynomial pass lower bounds for graph streaming algorithms")
  Member "maximizing social influence in nearly optimal time":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "time constrained adaptive influence maximization")
  Member "general truthfulness characterizations via convex analysis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an embedding framework for consistent polyhedral surrogates")
  Member "privately releasing conjunctions and the statistical query barrier":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "approximate mathbb f _2 sketching of valuation functions")
  Member "combinatorial auctions with decreasing marginal utilities":
    also connected through other hyperedges:
      - Hyperedge HE-5 (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)