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 "cluster based distributed augmented lagrangian algorithm for a class of constrained convex optimization problems"):
  Abstract: Author(s): Moradian, Hossein; Kia, Solmaz S | Abstract: We propose a distributed solution for a constrained convex optimization problem over a network of clustered agents each consisted of a set of subagents. The communication range of the clustered agents is such that they can form a connected undirected graph topology. The total cost in this optimization problem is the sum of the local convex cost of the subagents of each cluster. We seek a minimizer of this cost subject to a set of affine equality constraints, and a set of affine inequality constrains specifying the bounds on the decision variables if such bounds exist. Our proposed distributed algorithm is a novel continuous-time algorithm that is linked to the augmented Lagrangian approach. It converges asymptotically when the local cost functions are convex and exponentially when they are strongly convex and have Lipschitz gradients. For efficient communication and computation resource management, we only require the agents that are coupled through an equality constraint to form a communication topology to address that coupling in a distributed manner. We use an {\epsilon}-exact penalty function to address the inequality constraints, and drive an explicit lower bound on the penalty function weight to guarantee convergence to {\epsilon}-neighborhood of the global minimum value of the cost. We demonstrate our results via an optimal resource allocation problem for power generators, and an optimal multi-sensor deployment problem.

Includes members:
  Member "linear convergence rate of a class of distributed augmented lagrangian algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "djam distributed jacobi asynchronous method for learning personal models")
  Member "convergence analysis of saddle point problems in time varying wireless systems control theoretical approach":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "exponential stability of primal dual gradient dynamics with non strong convexity")
  Member "zero gradient sum algorithms for distributed convex optimization the continuous time case":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "distributed algorithms for solving convex inequalities")

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.MA(Multiagent Systems)