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 supermodular optimization framework for leader selection under link noise in linear multi agent systems"
  Abstract: In many applications of multi-agent systems (MAS), a set of leader agents acts as a control input to the remaining follower agents. In this paper, we introduce an analytical approach to selecting leader agents in order to minimize the total mean-square error of the follower agent states from their desired value in steady-state in the presence of noisy communication links. We show that the problem of choosing leaders in order to minimize this error can be solved using supermodular optimization techniques, leading to efficient algorithms that are within a provable bound of the optimum. We formulate two leader selection problems within our framework, namely the problem of choosing a fixed number of leaders to minimize the error, as well as the problem of choosing the minimum number of leaders to achieve a tolerated level of error. We study both leader selection criteria for different scenarios, including MAS with static topologies, topologies experiencing random link or node failures, switching topologies, and topologies that vary arbitrarily in time due to node mobility. In addition to providing provable bounds for all these cases, simulation results demonstrate that our approach outperforms other leader selection methods, such as node degree-based and random selection methods, and provides comparable performance to current state of the art algorithms.

Connected through hyperedge HE-1 (induced by source paper "current flow group closeness centrality for complex networks"):
  with members:
    - "kirchhoff index as a measure of edge centrality in weighted networks nearly linear time algorithms"
    - "scaling up group closeness maximization"
    - "estimating current flow closeness centrality with a multigrid laplacian solver"
    - "scalable betweenness centrality maximization via sampling"
    - "measuring and maximizing influence via random walk in social activity networks"
    - "a faster cutting plane method and its implications for combinatorial and convex optimization"
    - "absorbing random walk centrality theory and algorithms"
    - "axioms for centrality"

Connected through hyperedge HE-2 (induced by source paper "shifting opinions in a social network through leader selection"):
  with members:
    - "current flow group closeness centrality for complex networks"
    - "opinion dynamics with varying susceptibility to persuasion"
    - "opinion dynamics with stubborn agents"
    - "minimizing polarization and disagreement in social networks"
    - "from local averaging to emergent global behaviors the fundamental role of network interconnections"
    - "opinion maximization in social networks"
    - "an efficient parallel solver for sdd linear systems"
    - "submodular optimization with submodular cover and submodular knapsack constraints"

Connected through hyperedge HE-3 (induced by source paper "a sub modular receding horizon solution for mobile multi agent persistent monitoring"):
  with members:
    - "multi robot routing for persistent monitoring with latency constraints"
    - "combinatorial algorithms for control of biological regulatory networks"
    - "distributed submodular maximization with limited information"
    - "persistent monitoring of events with stochastic arrivals at multiple stations"

Connected through hyperedge HE-4 (induced by source paper "resilient assignment using redundant robots on transport networks with uncertain travel time"):
  with members:
    - "redundant robot assignment on graphs with uncertain edge costs"
    - "job selection in a network of autonomous uavs for delivery of goods"
    - "privacy preserving vehicle assignment for mobility on demand systems"
    - "adaptive submodularity theory and applications in active learning and stochastic optimization"
    - "efficient informative sensing using multiple robots"
    - "combinatorial auctions with decreasing marginal utilities"

Connected through hyperedge HE-5 (induced by source paper "distributed submodular minimization over networks a greedy column generation approach"):
  with members:
    - "distributed submodular maximization with limited information"
    - "reflection methods for user friendly submodular optimization"
    - "learning with submodular functions a convex optimization perspective"
    - "efficient minimization of decomposable submodular functions"
    - "structured sparsity inducing norms through submodular functions"
    - "distributed abstract optimization via constraints consensus theory and applications"

Connected through hyperedge HE-6 (induced by source paper "redundant robot assignment on graphs with uncertain edge costs"):
  with members:
    - "job selection in a network of autonomous uavs for delivery of goods"
    - "efficient informative sensing using multiple robots"
    - "combinatorial auctions with decreasing marginal utilities"

Connected through hyperedge HE-7 (induced by source paper "minimal reachability is hard to approximate"):
  with members:
    - "minimal inputs outputs for a networked system"
    - "minimal reachability problems"
    - "variable selection is hard"
    - "minimizing convergence error in multi agent systems via leader selection a supermodular optimization approach"
    - "controllability metrics limitations and algorithms for complex networks"
    - "optimal approximation for submodular and supermodular optimization with bounded curvature"

Connected through hyperedge HE-8 (induced by source paper "on the structure and computation of random walk times in finite graphs"):
  with members:
    - "optimal temporal logic planning in probabilistic semantic maps"
    - "minimizing convergence error in multi agent systems via leader selection a supermodular optimization approach"
    - "large scale spectral clustering using resistance distance and spielman teng solvers"
    - "opinion dynamics in social networks a local interaction game with stubborn agents"
    - "mdp optimal control under temporal logic constraints"

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)