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 parallel decomposition method for nonconvex stochastic multi agent optimization problems"):
  Abstract: This paper considers the problem of minimizing the expected value of a (possibly nonconvex) cost function parameterized by a random (vector) variable, when the expectation cannot be computed accurately (e.g., because the statistics of the random variables are unknown and/or the computational complexity is prohibitive). Classical stochastic gradient methods for solving this problem may suffer from slow convergence. In this paper, we propose a stochastic parallel Successive Convex Approximation-based (best-response) algorithm for general nonconvex stochastic sum-utility optimization problems, which arise naturally in the design of multi-agent networks. The proposed novel decomposition approach enables all users to update their optimization variables in parallel by solving a sequence of strongly convex subproblems, one for each user. Almost sure convergence to stationary points is proved. We then customize the algorithmic framework to solve the stochastic sum rate maximization problem over single-input-single-output (SISO) frequency-selective interference channels, multiple-input-multiple-output (MIMO) interference channels, and MIMO multiple-access channels. Numerical results corroborate that the proposed algorithms can converge faster than state-of-the-art stochastic gradient schemes while achieving the same (or better) sum-rates.

Includes members:
  Member "hybrid random deterministic parallel algorithms for nonconvex big data optimization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distributed partitioned big data optimization via asynchronous dual decomposition")
  Member "parallel selective algorithms for big data optimization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a randomized primal distributed algorithm for partitioned and big data non convex optimization")
  Member "decomposition by partial linearization parallel optimization of multi agent systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "convergent policy optimization for safe reinforcement learning")
  Member "real and complex monotone communication games":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on cyber risk management of blockchain networks a game theoretic approach")
  Member "averaged iterative water filling algorithm robustness and convergence":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "signal processing and optimal resource allocation for the interference channel")

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)