human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "approachability regret and calibration implications and equivalences"
  Abstract: Blackwell approachability, regret minimization and calibration are three criteria evaluating a strategy (or an algorithm) in different sequential decision problems, or repeated games between a player and Nature. Although they have at first sight nothing in common, links between have been discovered: both consistent and calibrated strategies can be constructed by following, in some auxiliary game, an approachability strategy. We gathered famous or recent results and provide new ones in order to develop and generalize Blackwell's elegant theory. The final goal is to show how it can be used as a basic powerful tool to exhibit a new class of intuitive algorithms, based on simple geometric properties. In order to be complete, we also prove that approachability can be seen as a byproduct of the very existence of consistent or calibrated strategies.

Connected through hyperedge HE-1 (induced by source paper "an approximate dynamic programming approach to repeated games with vector losses"):
  with members:
    - "towards optimal algorithms for prediction with expert advice"
    - "towards minimax online learning with unknown time horizon"
    - "regret analysis of stochastic and nonstochastic multi armed bandit problems"
    - "internal regret with partial monitoring calibration based optimal algorithms"
    - "approachability of convex sets in games with partial monitoring"

Connected through hyperedge HE-2 (induced by source paper "regret optimal strategies for playing repeated games with discounted losses"):
  with members:
    - "towards optimal algorithms for prediction with expert advice"
    - "towards minimax online learning with unknown time horizon"
    - "regret analysis of stochastic and nonstochastic multi armed bandit problems"
    - "prediction with expert advice under discounted loss"

Connected through hyperedge HE-3 (induced by source paper "repeated games with vector losses a set valued dynamic programming approach"):
  with members:
    - "towards optimal algorithms for prediction with expert advice"
    - "towards minimax online learning with unknown time horizon"
    - "regret analysis of stochastic and nonstochastic multi armed bandit problems"

Connected through hyperedge HE-4 (induced by source paper "approachability of convex sets in generalized quitting games"):
  with members:
    - "internal regret with partial monitoring calibration based optimal algorithms"
    - "approachability of convex sets in games with partial monitoring"

Connected through hyperedge HE-5 (induced by source paper "an online convex optimization approach to blackwell s approachability"):
  with members:
    - "introduction to online convex optimization"
    - "calibration and internal no regret with partial monitoring"

Question: Please tell me which class the center node 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)