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 bandit for energy efficient and delay sensitive edge computing in dynamic networks with uncertainty"):
  Abstract: In the emerging edge-computing paradigm, mobile devices offload the computational tasks to an edge server by routing the required data over the wireless network. The full potential of edge-computing becomes realized only if the devices select the most appropriate server in terms of the latency and energy consumption, among many available ones. This problem is, however, challenging due to the randomness of the environment and lack of prior information about the environment. Therefore, a smart device, which sequentially chooses a server under uncertainty, attempts to improve its decision based on the historical time- and energy consumption. The problem becomes more complicated in a dynamic environment, where key variables might undergo abrupt changes. To deal with the aforementioned problem, we first analyze the required time and energy to data transmission and processing. We then use the analysis to cast the problem as a budget-constrained multi-armed bandit problem, where each arm is associated with a reward and cost, with time-variant statistical characteristics. We propose a policy to solve the formulated bandit problem and prove a regret bound. The numerical results demonstrate the superiority of the proposed method compared to a number of existing solutions.

Includes members:
  Member "computation offloading and activation of mobile edge computing servers a minority game":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "an efficient mechanism for computation offloading in mobile edge computing")
  Member "multi armed bandits with application to 5g small cells":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "thirty years of machine learning the road to pareto optimal next generation wireless networks")
  Member "thompson sampling for budgeted multi armed bandits":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "online joint bid daily budget optimization of internet advertising campaigns")
  Member "optimization of radio and computational resources for energy efficiency in latency constrained application offloading":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "analysis on computation intensive status update in mobile edge computing")
  Member "knapsack based optimal policies for budget limited multi armed bandits":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "advances in bandits with knapsacks")
  Member "regret analysis of stochastic and nonstochastic multi armed bandit problems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "multi source domain adaptation for text classification via distancenet 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)