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 "repeated games with vector losses a set valued dynamic programming approach"):
  Abstract: We consider infinitely repeated games with vector losses discounted over time. We characterize the set of minimal upper bounds on expected losses that a player can simultaneously guarantee across the different dimensions. Specifically, we show that this set is the fixed point of a set-valued dynamic programming operator. This approach also characterizes the strategies that achieve these bounds. These optimal strategies are shown to be independent of the player's own past actions and stationary relative to a compact state space obtained by parameterizing the set of the minimal bounds. We also present a computational procedure to approximate this set and the optimal strategies. #R##N#We discuss two applications of our results: 1) characterization of the optimal strategy of the uninformed player in zero-sum discounted repeated games with incomplete information on one side; 2) characterization of the minmax optimal regret and the regret-optimal strategy in repeated games with discounted losses. Our approximation procedure can be used to compute approximately optimal strategies in both these applications. We illustrate this procedure by computing approximately regret-optimal strategies for the problem of prediction using expert advice from two and three experts under $\{0,1\}-$losses. Our numerical evaluations demonstrate improved performance over existing algorithms for this problem.

Includes members:
  Member "towards optimal algorithms for prediction with expert advice":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimal anytime regret with two experts")
  Member "approachability regret and calibration implications and equivalences":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an approximate dynamic programming approach to repeated games with vector losses")
  Member "towards minimax online learning with unknown time horizon":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimal anytime regret with two experts")
  Member "regret analysis of stochastic and nonstochastic multi armed bandit problems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (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.GT(Computer Science and Game Theory)