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 "resilient consensus for multi agent systems subject to differential privacy requirements"):
  Abstract: We consider multi-agent systems interacting over directed network topologies where a subset of agents is adversary/faulty and where the non-faulty agents have the goal of reaching consensus, while fulfilling a differential privacy requirement on their initial conditions. In order to address this problem, we develop an update law for the non-faulty agents. Specifically, we propose a modification of the so called Mean-Subsequence-Reduced (MSR) algorithm, the Differentially Private MSR (DP-MSR) algorithm, and characterize three important properties of the algorithm: correctness, accuracy and differential privacy. We show that if the network topology is $(2f +1)$-robust, then the algorithm allows the non-faulty agents to reach consensus despite the presence of up to $f$ faulty agents and we characterize the accuracy of the algorithm. Furthermore, we also show that in two special cases our distributed algorithm can be tuned to guarantees differential privacy of the initial conditions and the differential privacy requirement is related to the maximum network degree. The results are illustrated via simulations.

Includes members:
  Member "resilient consensus of second order agent networks asynchronous update rules with delays":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "determining r and r s robustness of digraphs using mixed integer linear programming")
  Member "resilient randomized quantized consensus":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "determining r and r s robustness of digraphs using mixed integer linear programming")
  Member "r robustness and r s robustness of circulant graphs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "determining r and r s robustness of digraphs using mixed integer linear programming")
  Member "exploiting nodes symmetries to control synchronization and consensus patterns in multiagent systems":
    also connected through other hyperedges:
      (none)
  Member "a jamming resilient algorithm for self triggered network coordination":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "state of the art of cyber physical systems security an automatic control perspective")
  Member "reaching approximate byzantine consensus with multi hop communication":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "determining r and r s robustness of digraphs using mixed integer linear programming")
  Member "differentially private distributed optimization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "asynchronous federated learning with differential privacy for edge intelligence")
  Member "differentially private iterative synchronous consensus":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "privacy preserving distributed machine learning via local randomization and admm perturbation")

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)