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 "collaborative learning with limited interaction tight bounds for distributed exploration in multi armed bandits"):
  Abstract: Best arm identification (or, pure exploration) in multi-armed bandits is a fundamental problem in machine learning. In this paper we study the distributed version of this problem where we have multiple agents, and they want to learn the best arm collaboratively. We want to quantify the power of collaboration under limited interaction (or, communication steps), as interaction is expensive in many settings. We measure the running time of a distributed algorithm as the speedup over the best centralized algorithm where there is only one agent. We give almost tight round-speedup tradeoffs for this problem, along which we develop several new techniques for proving lower bounds on the number of communication steps under time or confidence constraints.

Includes members:
  Member "improved algorithms for collaborative pac learning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "tight bounds for collaborative pac learning via multiplicative weights")
  Member "tight bounds for collaborative pac learning via multiplicative weights":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "improved algorithms for collaborative pac learning")
  Member "adaptive multiple arm identification":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "thresholding bandit problem with both duels and pulls")
  Member "towards instance optimal bounds for best arm identification":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "thresholding bandit with optimal aggregate regret")
  Member "delay and cooperation in nonstochastic bandits":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the gossiping insert eliminate algorithm for multi agent bandits")
  Member "multi player bandits a musical chairs approach":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "my fair bandit distributed learning of max min fairness with multi player bandits")
  Member "on distributed cooperative decision making in multiarmed bandits":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a decentralized communication policy for multi agent multi armed bandit problems")
  Member "distributed exploration in multi armed bandits":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "the gossiping insert eliminate algorithm for multi agent bandits")

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.LG(Machine Learning)