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: "sensor management for multi target tracking via multi bernoulli filtering"
  Abstract: Abstract   In multi-object stochastic systems, the issue of sensor management is a theoretically and computationally challenging problem. In this paper, we present a novel random finite set (RFS) approach to the multi-target sensor management problem within the partially observed Markov decision process (POMDP) framework. The multi-target state is modelled as a multi-Bernoulli RFS, and the multi-Bernoulli filter is used in conjunction with two different control objectives: maximizing the expected Renyi divergence between the predicted and updated densities, and minimizing the expected posterior cardinality variance. Numerical studies are presented in two scenarios where a mobile sensor tracks five moving targets with different levels of observability.

Connected through hyperedge HE-1 (induced by source paper "multi objective multi agent planning for jointly discovering and tracking mobile object"):
  with members:
    - "trackerbots autonomous unmanned aerial vehicle for real time localization and tracking of multiple radio tagged animals"
    - "trackerbots autonomous unmanned aerial vehicle for real time localization and tracking of multiple radio tagged animals"
    - "online uav path planning for joint detection and tracking of multiple radio tagged objects"

Connected through hyperedge HE-2 (induced by source paper "multi sensor control for multi object bayes filters"):
  with members:
    - "distributed fusion with multi bernoulli filter based on generalized covariance intersection"
    - "multi bernoulli sensor control via minimization of expected estimation errors"
    - "sensor control for multi object tracking using labeled multi bernoulli filter"
    - "the cauchy schwarz divergence for poisson point processes"
    - "consensus labeled random finite set filtering for distributed multi object tracking"
    - "on the finite time convergence of cyclic coordinate descent methods"

Connected through hyperedge HE-3 (induced by source paper "online uav path planning for joint detection and tracking of multiple radio tagged objects"):
  with members:
    - "trackerbots autonomous unmanned aerial vehicle for real time localization and tracking of multiple radio tagged animals"
    - "trackerbots autonomous unmanned aerial vehicle for real time localization and tracking of multiple radio tagged animals"
    - "multi sensor control for multi object bayes filters"
    - "the cauchy schwarz divergence for poisson point processes"

Connected through hyperedge HE-4 (induced by source paper "statistical information fusion for multiple view sensor data in multi object tracking"):
  with members:
    - "distributed fusion with multi bernoulli filter based on generalized covariance intersection"
    - "multi bernoulli sensor control via minimization of expected estimation errors"
    - "the cauchy schwarz divergence for poisson point processes"

Connected through hyperedge HE-5 (induced by source paper "multi sensor control for multi target tracking using cauchy schwarz divergence"):
  with members:
    - "multi bernoulli sensor control via minimization of expected estimation errors"
    - "the cauchy schwarz divergence for poisson point processes"
    - "consensus labeled random finite set filtering for distributed multi object tracking"

Connected through hyperedge HE-6 (induced by source paper "multi bernoulli sensor control via minimization of expected estimation errors"):
  with members:
    - "the cauchy schwarz divergence for poisson point processes"

Connected through hyperedge HE-7 (induced by source paper "the cauchy schwarz divergence for poisson point processes"):
  with members:
    - "powers of tensors and fast matrix multiplication"

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)