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 "on optimality of adaptive linear quadratic regulators"):
  Abstract: Adaptive regulation of linear systems represents a canonical problem in stochastic control. Performance of adaptive control policies is assessed through the regret with respect to the optimal regulator, that reflects the increase in the operating cost due to uncertainty about the parameters that drive the dynamics of the system. However, available results in the literature do not provide a sharp quantitative characterization of the effect of the unknown dynamics parameters on the regret. Further, there are issues on how easy it is to implement the adaptive policies proposed in the literature. Finally, results regarding the accuracy that the system's parameters are identified are scarce and rather incomplete. #R##N#This study aims to comprehensively address these three issues. First, by introducing a novel decomposition of adaptive policies, we establish a sharp expression for the regret of an arbitrary policy in terms of the deviations from the optimal regulator. Second, we show that adaptive policies based on a slight modification of the widely used Certainty Equivalence scheme are optimal. Specifically, we establish a regret of (nearly) square-root rate for two families of randomized adaptive policies. The presented regret bounds are obtained by using anti-concentration results on the random matrices employed when randomizing the estimates of the unknown dynamics parameters. Moreover, we study the minimal additional information needed on dynamics matrices for which the regret will become of logarithmic order. Finally, the rate at which the unknown parameters of the system are being identified is specified for the proposed adaptive policies.

Includes members:
  Member "learning without mixing towards a sharp analysis of linear system identification":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "improper learning for non stochastic control")
  Member "finite time analysis of optimal adaptive policies for linear quadratic systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "regret bounds for decentralized learning in cooperative multi agent dynamical systems")
  Member "finite time identification in unstable linear systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "non asymptotic and accurate learning of nonlinear dynamical systems")
  Member "optimality of fast matching algorithms for random networks with applications to structural controllability":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "topological controllability of undirected networks of diffusively coupled agents")

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.SY(Systems and Control)