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: "the cauchy schwarz divergence for poisson point processes"
  Abstract: Information theoretic divergences are fundamental tools used to measure the difference between the information conveyed by two random processes. In this paper, we show that the Cauchy-Schwarz divergence between two Poisson point processes is the half the squared L 2 -distance between their respective intensity functions. Moreover, this can be evaluated in closed form when the intensities are Gaussian mixtures.

Connected through hyperedge HE-1 (induced by source paper "decentralized multi target tracking in urban environments overview and challenges"):
  with members:
    - "towards search based motion planning for micro aerial vehicles"
    - "search based motion planning for quadrotors using linear quadratic minimum time control"
    - "sensor selection for target tracking in wireless sensor networks with uncertainty"
    - "information acquisition with sensing robots algorithms and error bounds"
    - "cooperative multi target localization with noisy sensors"
    - "point based pomdp algorithms improved analysis and implementation"
    - "efficient informative sensing using multiple robots"

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"
    - "robust distributed fusion with labeled random finite sets"
    - "distributed smc phd fusion for partial arithmetic average consensus"
    - "distributed fusion with multi bernoulli filter based on generalized covariance intersection"
    - "consensus labeled random finite set filtering for distributed multi object tracking"

Connected through hyperedge HE-3 (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"
    - "consensus labeled random finite set filtering for distributed multi object tracking"
    - "sensor management for multi target tracking via multi bernoulli filtering"
    - "on the finite time convergence of cyclic coordinate descent methods"

Connected through hyperedge HE-4 (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"
    - "sensor management for multi target tracking via multi bernoulli filtering"

Connected through hyperedge HE-5 (induced by source paper "distributed smc phd fusion for partial arithmetic average consensus"):
  with members:
    - "partial consensus and conservative fusion of gaussian mixtures for distributed phd fusion"
    - "a scalable algorithm for tracking an unknown number of targets using multiple sensors"
    - "distributed bayesian filtering using logarithmic opinion pool for dynamic sensor networks"

Connected through hyperedge HE-6 (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"
    - "sensor management for multi target tracking via multi bernoulli filtering"

Connected through hyperedge HE-7 (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"
    - "consensus labeled random finite set filtering for distributed multi object tracking"
    - "sensor management for multi target tracking via multi bernoulli filtering"

Connected through hyperedge HE-8 (induced by source paper "multi bernoulli sensor control via minimization of expected estimation errors"):
  with members:
    - "sensor management for multi target tracking via multi bernoulli filtering"

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.IT(Information Theory)