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 "constraint coupled distributed optimization a relaxation and duality approach"):
  Abstract: In this paper we consider a distributed optimization scenario in which agents of a network want to minimize the sum of local convex cost functions, each one depending on a local variable, subject to convex local and coupling constraints, with the latter involving all the decision variables. We propose a novel distributed algorithm based on a relaxation of the primal problem and an elegant exploration of duality theory. Despite its complex derivation, based on several duality steps, the distributed algorithm has a very simple and intuitive structure. That is, each node finds a primal-dual optimal solution pair of a local, relaxed version of the original problem, and then linearly updates other dual variables. We prove that agents' estimates asymptotically converge to an optimal solution of the given problem, namely to a point satisfying both local and coupling constraints and having optimal cost. This primal recovery property is obtained without any averaging mechanism typically used in dual methods. To corroborate the theoretical results, we show how the methodology applies to an instance of a Distributed Model Predictive Control scheme in a microgrid control scenario.

Includes members:
  Member "a duality based approach for distributed optimization with coupling constraints":
    also connected through other hyperedges:
      (none)
  Member "next in network nonconvex optimization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "gradient tracking and variance reduction for decentralized optimization and machine learning")
  Member "asynchronous distributed optimization via randomized dual proximal gradient":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "asyspa an exact asynchronous algorithm for convex optimization over digraphs")
  Member "multi agent distributed optimization via inexact consensus admm":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "distributed dual coordinate ascent in general tree networks and its application in federated learning")
  Member "a polyhedral approximation framework for convex and robust distributed optimization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a duality based approach for distributed optimization with coupling constraints")
  Member "distributed constrained optimization by consensus based primal dual perturbation method":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "grand challenges of resilience autonomous system resilience through design and runtime measures")
  Member "fast distributed gradient methods":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on local computation for optimization in multi agent systems")

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)