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: "r robustness and r s robustness of circulant graphs"
  Abstract: There has been recent growing interest in graph theoretical properties known as r- and (r,s)-robustness. These properties serve as sufficient conditions guaranteeing the success of certain consensus algorithms in networks with misbehaving agents present. Due to the complexity of determining the robustness for an arbitrary graph, several methods have previously been proposed for identifying the robustness of specific classes of graphs or constructing graphs with specified robustness levels. The majority of such approaches have focused on undirected graphs. In this paper we identify a class of scalable directed graphs whose edge set is determined by a parameter k and prove that the robustness of these graphs is also determined by k. We support our results through computer simulations.

Connected through hyperedge HE-1 (induced by source paper "determining r and r s robustness of digraphs using mixed integer linear programming"):
  with members:
    - "determining r robustness of arbitrary digraphs using zero one linear integer programming"
    - "secure distributed state estimation of an lti system over time varying networks and analog erasure channels"
    - "resilient consensus of second order agent networks asynchronous update rules with delays"
    - "on connectivity and robustness in random intersection graphs"
    - "resilient randomized quantized consensus"
    - "distributed optimization under adversarial nodes"
    - "robustness and algebraic connectivity of random interdependent networks"
    - "asynchronous convex consensus in the presence of crash faults"

Connected through hyperedge HE-2 (induced by source paper "resilient consensus for multi agent systems subject to differential privacy requirements"):
  with members:
    - "resilient consensus of second order agent networks asynchronous update rules with delays"
    - "resilient randomized quantized consensus"
    - "exploiting nodes symmetries to control synchronization and consensus patterns in multiagent systems"
    - "a jamming resilient algorithm for self triggered network coordination"
    - "reaching approximate byzantine consensus with multi hop communication"
    - "differentially private distributed optimization"
    - "differentially private iterative synchronous consensus"
    - "calibrating data to sensitivity in private data analysis"

Connected through hyperedge HE-3 (induced by source paper "resilient consensus through asynchronous event based communication"):
  with members:
    - "resilient consensus of second order agent networks asynchronous update rules with delays"
    - "resilient randomized quantized consensus"
    - "distributed optimization under adversarial nodes"
    - "iterative approximate byzantine consensus in arbitrary directed graphs"

Connected through hyperedge HE-4 (induced by source paper "resilient leader follower consensus to arbitrary reference values"):
  with members:
    - "secure distributed state estimation of an lti system over time varying networks and analog erasure channels"
    - "resilient consensus of second order agent networks asynchronous update rules with delays"
    - "resilient continuous time consensus in fractional robust networks"
    - "robustness of information diffusion algorithms to locally bounded adversaries"

Connected through hyperedge HE-5 (induced by source paper "resilience against misbehaving nodes in asynchronous networks"):
  with members:
    - "resilient consensus of second order agent networks asynchronous update rules with delays"
    - "resilient randomized quantized consensus"
    - "robust self triggered coordination with ternary controllers"

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)