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 "micky a cheaper alternative for selecting cloud instances"):
  Abstract: Most cloud computing optimizers explore and improve one workload at a time. When optimizing many workloads, the single-optimizer approach can be prohibitively expensive. Accordingly, we examine "collective optimizer" that concurrently explore and improve a set of workloads significantly reducing the measurement costs. Our large-scale empirical study shows that there is often a single cloud configuration which is surprisingly near-optimal for most workloads. Consequently, we create a collective-optimizer, MICKY, that reformulates the task of finding the near-optimal cloud configuration as a multi-armed bandit problem. MICKY efficiently balances exploration (of new cloud configurations) and exploitation (of known good cloud configuration). Our experiments show that MICKY can achieve on average 8.6 times reduction in measurement cost as compared to the state-of-the-art method while finding near-optimal solutions. #R##N#Hence we propose MICKY as the basis of a practical collective optimization method for finding good cloud configurations (based on various constraints such as budget and tolerance to near-optimal configurations).

Includes members:
  Member "finding faster configurations using flash":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "learning software configuration spaces a systematic literature review")
  Member "scout an experienced guide to find the best cloud configuration":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "whence to learn transferring knowledge in configurable systems using beetle")
  Member "using bad learners to find good configurations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "towards quality assurance of software product lines with adversarial configurations")
  Member "bestconfig tapping the performance potential of systems via automatic configuration tuning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "black or white how to develop an autotuner for memory based analytics extended version")
  Member "fast bayesian optimization of machine learning hyperparameters on large datasets":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a system for massively parallel hyperparameter tuning")
  Member "cloud migration a case study of migrating an enterprise it system to iaas":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "recent developments in cloud based systems state of art")
  Member "reinforcement learning a survey":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "online fast adaptation and knowledge accumulation a new approach to continual learning")

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.DC(Distributed, Parallel, and Cluster Computing)