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 "stable predictive optimistic counterfactual regret minimization"):
  Abstract: The CFR framework has been a powerful tool for solving large-scale extensive-form games in practice. However, the theoretical rate at which past CFR-based algorithms converge to the Nash equilibrium is on the order of $O(T^{-1/2})$, where $T$ is the number of iterations. In contrast, first-order methods can be used to achieve a $O(T^{-1})$ dependence on iterations, yet these methods have been less successful in practice. In this work we present the first CFR variant that breaks the square-root dependence on iterations. By combining and extending recent advances on predictive and stable regret minimizers for the matrix-game setting we show that it is possible to leverage "optimistic" regret minimizers to achieve a $O(T^{-3/4})$ convergence rate within CFR. This is achieved by introducing a new notion of stable-predictivity, and by setting the stability of each counterfactual regret minimizer relative to its location in the decision tree. Experiments show that this method is faster than the original CFR algorithm, although not as fast as newer variants, in spite of their worst-case $O(T^{-1/2})$ dependence on iterations.

Includes members:
  Member "regret circuits composability of regret minimizers":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "stochastic regret minimization in extensive form games")
  Member "acceleration through optimistic no regret dynamics":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "curvature of feasible sets in offline and online optimization")
  Member "solving imperfect information games via discounted regret minimization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "stochastic regret minimization in extensive form games")
  Member "solving large sequential games with the excessive gap technique":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "increasing iterate averaging for solving saddle point problems")
  Member "online convex optimization for sequential decision processes and extensive form games":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "stochastic regret minimization in extensive form games")
  Member "depth limited solving for imperfect information games":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "single deep counterfactual regret minimization")
  Member "safe and nested subgame solving for imperfect information games":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "coordination in adversarial sequential team games via multi agent deep reinforcement learning")
  Member "deepstack expert level artificial intelligence in heads up no limit poker":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "learning zero sum simultaneous move markov games using function approximation and correlated equilibrium")

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)