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 "prediction with expert advice under discounted loss"):
  Abstract: We study prediction with expert advice in the setting where the losses are accumulated with some discounting---the impact of old losses may gradually vanish. We generalize the Aggregating Algorithm and the Aggregating Algorithm for Regression to this case, propose a suitable new variant of exponential weights algorithm, and prove respective loss bounds.

Includes members:
  Member "prediction with advice of unknown number of experts":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a modern introduction to online learning")
  Member "on line prediction with kernels and the complexity approximation principle":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an empirical comparison of algorithms for aggregating expert predictions")
  Member "supermartingales in prediction with expert advice":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "metagrad multiple learning rates in online learning")
  Member "a parameter free hedging algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a modern introduction to online learning")
  Member "a new hedging algorithm and its application to inferring latent random variables":
    also connected through other hyperedges:
      (none)
  Member "on line regression competitive with reproducing kernel hilbert spaces":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "locally adaptive nonparametric online 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.LG(Machine Learning)