human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "a proximal dual consensus admm method for multi agent constrained optimization"
  Abstract: This paper considers a convex optimization problem with a globally coupled linear equality constraint and local polyhedron constraints and develops efficient distributed optimization methods. The considered problem has many engineering applications. Due to the polyhedron constraints, agents in the existing methods have to deal with polyhedron constrained subproblems at each iteration. One of the key challenges is that projection onto a polyhedron set is not trivial, which prohibits the agents from solving these subproblems efficiently. In this paper, based on the alternating direction method of multipliers (ADMM), we propose a new distributed optimization method, called proximal dual consensus ADMM (PDC-ADMM). The PDC-ADMM transforms the polyhedron constraints as quadratic penalty terms in the subproblems, making the subproblems efficiently solvable and consequently reducing the overall computational overhead of the agents. In addition, we propose a randomized PDC-ADMM which can deal with time-varying networks with randomly  on/off  agents and communication errors, and an inexact (randomized) PDC-ADMM for low-complexity computations. We show that the proposed distributed methods converge to the optimal solution set almost surely and have a   $\mathcal{O}\left(1/k\right)$   ergodic convergence rate in the mean. Numerical results show that the proposed methods offer significantly lower computation time than the existing distributed ADMM method in solving a linearly constrained LASSO problem.

Connected through hyperedge HE-1 (induced by source paper "truthful and faithful monetary policy for a stablecoin conducted by a decentralised encrypted artificial intelligence"):
  with members:
    - "helen maliciously secure coopetitive learning for linear models"
    - "how to make a digital currency on a blockchain stable"

Connected through hyperedge HE-2 (induced by source paper "hvac energy cost optimization for a multi zone building via a decentralized approach"):
  with members:
    - "decentralized and distributed temperature control via hvac systems in energy efficient buildings"
    - "distributed real time hvac control for cost efficient commercial buildings under smart grid environment"

Connected through hyperedge HE-3 (induced by source paper "a duality based approach for distributed optimization with coupling constraints"):
  with members:
    - "a duality based approach for distributed min max optimization with application to demand side management"
    - "a polyhedral approximation framework for convex and robust distributed optimization"
    - "distributed constrained optimization by consensus based primal dual perturbation method"

Connected through hyperedge HE-4 (induced by source paper "a distributed asynchronous and incremental algorithm for nonconvex optimization an admm based approach"):
  with members:
    - "parallel algorithms for constrained tensor factorization via alternating direction method of multipliers"
    - "saga a fast incremental gradient method with support for non strongly convex composite objectives"
    - "sparse inverse covariance selection via alternating linearization methods"
    - "optimal linear precoding strategies for wideband noncooperative systems based on game theory part i nash equilibria"

Question: Please tell me which class the center node 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)