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: "controllability metrics limitations and algorithms for complex networks"
  Abstract: This paper studies the problem of controlling complex networks, that is, the joint problem of selecting a set of control nodes and of designing a control input to steer a network to a target state. For this problem (i) we propose a metric to quantify the difficulty of the control problem as a function of the required control energy, (ii) we derive bounds based on the system dynamics (network topology and weights) to characterize the tradeoff between the control energy and the number of control nodes, and (iii) we propose an open-loop control strategy with performance guarantees. In our strategy we select control nodes by relying on network partitioning, and we design the control input by leveraging optimal and distributed control techniques. Our findings show several control limitations and properties. For instance, for Schur stable and symmetric networks: (i) if the number of control nodes is constant, then the control energy increases exponentially with the number of network nodes, (ii) if the number of control nodes is a fixed fraction of the network nodes, then certain networks can be controlled with constant energy independently of the network dimension, and (iii) clustered networks may be easier to control because, for sufficiently many control nodes, the control energy depends only on the controllability properties of the clusters and on their coupling strength. We validate our results with examples from power networks, social networks, and epidemics spreading.

Connected through hyperedge HE-1 (induced by source paper "controllability of bandlimited graph processes over random time varying graphs"):
  with members:
    - "localized linear regression in networked data"
    - "greedy sampling of graph signals"
    - "adaptive graph signal processing algorithms and optimal sampling strategies"
    - "autoregressive moving average graph filtering"
    - "filtering random graph processes over random time varying graphs"
    - "rethinking sketching as sampling a graph signal processing approach"
    - "reconstruction of graph signals through percolation from seeding nodes"
    - "learning heat diffusion graphs"

Connected through hyperedge HE-2 (induced by source paper "on almost controllability of dynamical complex networks with noises"):
  with members:
    - "on performance of peer review for academic journals analysis based on distributed parallel system"
    - "dynamic output feedback guaranteed cost synchronization for multiagent networks with given cost budgets"
    - "completely distributed guaranteed performance consensualization for high order multiagent systems with switching topologies"
    - "on quantitatively measuring controllability of complex networks"

Connected through hyperedge HE-3 (induced by source paper "functional target controllability of networks structural properties and efficient algorithms"):
  with members:
    - "minimum energy control for complex networks"
    - "the observability radius of networks"
    - "energy scaling of targeted optimal control of complex networks"
    - "gramian based reachability metrics for bilinear networks"

Connected through hyperedge HE-4 (induced by source paper "controllability gramian submatrices for a network consensus model"):
  with members:
    - "sign patterns of inverse doubly nonnegative matrices"
    - "energy scaling of targeted optimal control of complex networks"
    - "controllability of networked mimo systems"

Connected through hyperedge HE-5 (induced by source paper "measure of quality of finite dimensional linear systems a frame theoretic view"):
  with members:
    - "optimal dictionary for least squares representation"
    - "gramian based reachability metrics for bilinear networks"

Connected through hyperedge HE-6 (induced by source paper "on the trade off between controllability and robustness in networks of diffusively coupled agents"):
  with members:
    - "graph distances and controllability of networks"

Connected through hyperedge HE-7 (induced by source paper "resilience in multi robot target tracking through reconfiguration"):
  with members:
    - "resilience by reconfiguration exploiting heterogeneity in robot teams"

Connected through hyperedge HE-8 (induced by source paper "deterministic and randomized actuator scheduling with guaranteed performance bounds"):
  with members:
    - "an alon boppana type bound for weighted graphs and lowerbounds for spectral sparsification"
    - "an sdp based algorithm for linear sized spectral sparsification"
    - "minimal reachability is hard to approximate"
    - "structural analysis and optimal design of distributed system throttlers"
    - "control principles of complex networks"
    - "graph distances and controllability of networks"
    - "minimal reachability problems"
    - "near optimal column based matrix reconstruction"

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.SY(Systems and Control)