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: "robust distributed fusion with labeled random finite sets"
  Abstract: This paper considers the problem of the distributed fusion of multiobject posteriors in the labeled random finite set filtering framework, using a generalized covariance intersection (GCI) method. Our analysis shows that GCI fusion with labeled multiobject densities strongly relies on label consistencies between local multiobject posteriors at different sensor nodes, and hence suffers from a severe performance degradation when perfect label consistencies are violated. Moreover, we mathematically analyze this phenomenon from the perspective of the principle of minimum discrimination information and the so-called yes-object probability. Inspired by the analysis, we propose a novel and general solution for the distributed fusion with labeled multiobject densities that is robust to label inconsistencies between sensors. Specifically, the labeled multiobject posteriors are first marginalized to their unlabeled posteriors, which are then fused using the GCI method. We also introduce a principled method to construct the labeled fused density and produce tracks formally. Based on the developed theoretical framework, we present tractable algorithms for the family of generalized labeled multi-Bernoulli (GLMB) filters including    $\delta$  -GLMB, marginalized    $\delta$  -GLMB, and labeled multi-Bernoulli filters. The robustness and efficiency of the proposed distributed fusion algorithm are demonstrated in challenging tracking scenarios via numerical experiments.

Connected through hyperedge HE-1 (induced by source paper "decentralized poisson multi bernoulli filtering for vehicle tracking"):
  with members:
    - "poisson multi bernoulli mixture filter direct derivation and implementation"
    - "mono camera 3d multi object tracking using deep learning detections and pmbm filtering"
    - "generalized optimal sub pattern assignment metric"
    - "multisensor poisson multi bernoulli filter for joint target sensor state tracking"
    - "distributed fusion with multi bernoulli filter based on generalized covariance intersection"
    - "extended object tracking introduction overview and applications"
    - "a metric on the space of finite sets of trajectories for evaluation of multi target tracking algorithms"
    - "marginal multi bernoulli filters rfs derivation of mht jipda and association based member"

Connected through hyperedge HE-2 (induced by source paper "multiobject fusion with minimum information loss"):
  with members:
    - "partial consensus and conservative fusion of gaussian mixtures for distributed phd fusion"
    - "second order statistics analysis and comparison between arithmetic and geometric average fusion application to multi sensor target tracking"
    - "distributed smc phd fusion for partial arithmetic average consensus"
    - "distributed fusion with multi bernoulli filter based on generalized covariance intersection"
    - "the cauchy schwarz divergence for poisson point processes"
    - "consensus labeled random finite set filtering for distributed multi object tracking"

Connected through hyperedge HE-3 (induced by source paper "partial consensus and conservative fusion of gaussian mixtures for distributed phd fusion"):
  with members:
    - "distributed smc phd fusion for partial arithmetic average consensus"
    - "a scalable algorithm for tracking an unknown number of targets using multiple sensors"
    - "distributed fusion with multi bernoulli filter based on generalized covariance intersection"
    - "sigma point belief propagation"
    - "diffusion adaptation over networks"

Connected through hyperedge HE-4 (induced by source paper "distributed joint sensor registration and multitarget tracking via sensor network"):
  with members:
    - "distributed fusion with multi bernoulli filter based on generalized covariance intersection"
    - "distributed on line multidimensional scaling for self localization in wireless sensor networks"
    - "simultaneous distributed sensor self localization and target tracking using belief propagation and likelihood consensus"
    - "distributed sensor localization in random environments using minimal number of anchor nodes"

Connected through hyperedge HE-5 (induced by source paper "distributed multi sensor multi view fusion based on generalized covariance intersection"):
  with members:
    - "an overview of particle methods for random finite set models"
    - "multi target tracking in distributed sensor networks using particle phd filters"

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)