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 "multi armed bandits with application to 5g small cells"):
  Abstract: Due to the pervasive demand for mobile services, next generation wireless networks are expected to be able to deliver high data rates while wireless resources become more and more scarce. This requires the next generation wireless networks to move toward new networking paradigms that are able to efficiently support resource-demanding applications such as personalized mobile services. Examples of such paradigms foreseen for the emerging 5G cellular networks include very densely deployed small cells and device-to-device communications. For 5G networks, it will be imperative to search for spectrum and energy-efficient solutions to the resource allocation problems that i) are amenable to distributed implementation, ii) are capable of dealing with uncertainty and lack of information, and iii) can cope with users’ selfishness. The core objective of this article is to investigate and establish the potential of the MAB framework to address this challenge. In particular, we provide a brief tutorial on bandit problems, including different variations and solution approaches. Furthermore, we discuss recent applications as well as future research directions. In addition, we provide a detailed example of using an MAB model for energy-efficient small cell activation in 5G networks.

Includes members:
  Member "multi access communications with energy harvesting a multi armed bandit model and the optimality of the myopic policy":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distributed power control for large energy harvesting networks a multi agent deep reinforcement learning approach")
  Member "joint channel selection and power control in infrastructureless wireless networks a multiplayer multiarmed bandit framework":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "ballooning multi armed bandits")
  Member "channel selection for network assisted d2d communication via no regret bandit learning with calibrated forecasting":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multi armed bandits for decentralized ap selection in enterprise wlans")
  Member "evolution toward 5g multi tier cellular wireless networks an interference management perspective":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a survey on the security and the evolution of osmotic and catalytic computing for 5g networks")
  Member "regret analysis of stochastic and nonstochastic multi armed bandit problems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multi source domain adaptation for text classification via distancenet bandits")
  Member "approximation algorithms for restless bandit problems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "regime switching 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)