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 "a new approach for distributed hypothesis testing with extensions to byzantine resilience"):
  Abstract: We study a setting where a group of agents, each receiving partially informative private observations, seek to collaboratively learn the true state (among a set of hypotheses) that explains their joint observation profiles over time. To solve this problem, we propose a distributed learning rule that differs fundamentally from existing approaches, in the sense, that it does not employ any form of "belief-averaging". Specifically, every agent maintains a local belief (on each hypothesis) that is updated in a Bayesian manner without any network influence, and an actual belief that is updated (up to normalization) as the minimum of its own local belief and the actual beliefs of its neighbors. Under minimal requirements on the signal structures of the agents and the underlying communication graph, we establish consistency of the proposed belief update rule, i.e., we show that the actual beliefs of the agents asymptotically concentrate on the true state almost surely. As one of the key benefits of our approach, we show that our learning rule can be extended to scenarios that capture misbehavior on the part of certain agents in the network, modeled via the Byzantine adversary model. In particular, we prove that each non-adversarial agent can asymptotically learn the true state of the world almost surely, under appropriate conditions on the observation model and the network topology.

Includes members:
  Member "byzantine resilient distributed observers for lti systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "byzantine fault tolerant distributed linear regression")
  Member "distributed observers for lti systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a distributed observer for a discrete time linear system")
  Member "defending non bayesian learning against adversarial attacks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fall of empires breaking byzantine tolerant sgd by inner product manipulation")
  Member "distributed optimization under adversarial nodes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "resilient cyberphysical systems and their application drivers a technology roadmap")
  Member "exponentially fast parameter estimation in networks using distributed dual averaging":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "non bayesian social learning with uncertain models")
  Member "matrix representation of iterative approximate byzantine consensus in directed graphs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "resilient consensus for multi agent systems subject to differential privacy requirements")
  Member "iterative approximate byzantine consensus in arbitrary directed graphs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "grand challenges of resilience autonomous system resilience through design and runtime measures")

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)