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 resource aware approach to collaborative loop closure detection with provable performance guarantees"
  Abstract: This paper presents resource-aware algorithms for distributed inter-robot loop closure detection for applications such as collaborative simultaneous localization and mapping (CSLAM) and distributed image retrieval. In real-world scenarios, this process is resource-intensive as it involves exchanging many observations and geometrically verifying a large number of potential matches. This poses severe challenges for small-size and low-cost robots with various operational and resource constraints that limit, e.g., energy consumption, communication bandwidth, and computation capacity. This paper proposes a framework in which robots first exchange compact queries to identify a set of potential loop closures. We then seek to select a subset of potential inter-robot loop closures for geometric verification that maximizes a monotone submodular performance metric without exceeding budgets on computation (number of geometric verifications) and communication (amount of exchanged data for geometric verification). We demonstrate that this problem is in general NP-hard, and present efficient approximation algorithms with provable performance guarantees. The proposed framework is extensively evaluated on real and synthetic datasets. A natural convex relaxation scheme is also presented to certify the near-optimal performance of the proposed framework in practice.

Connected through hyperedge HE-1 (induced by source paper "door slam distributed online and outlier resilient slam for robotic teams"):
  with members:
    - "active rendezvous for multi robot pose graph optimization using sensing over wi fi"
    - "convex relaxations for pose graph optimization with outliers"
    - "near optimal budgeted data exchange for distributed loop closure detection"
    - "modeling perceptual aliasing in slam via discrete continuous graphical models"
    - "talk resource efficiently to me optimal communication planning for distributed loop closure detection"
    - "data efficient decentralized visual slam"
    - "distributed mapping with privacy and communication constraints lightweight algorithms and object based models"
    - "netvlad cnn architecture for weakly supervised place recognition"

Connected through hyperedge HE-2 (induced by source paper "measurement scheduling for cooperative localization in resource constrained conditions"):
  with members:
    - "cooperative localization under limited connectivity"
    - "data efficient decentralized visual slam"
    - "scheduling nonlinear sensors for stochastic process estimation"
    - "server assisted distributed cooperative localization over unreliable communication links"
    - "cooperative localization for mobile agents a recursive decentralized algorithm based on kalman filter decoupling"

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.RO(Robotics)