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: "autonomous 20 drone via pose estimation core sets"
  Abstract: How can we track an object such as toy micro quadcopter in real-time using home-made tracking system? We constructed a low-cost home-made tracking system ($<\$100$) based on web-cams and "Internet of Things" mini-board that is able to track popular toy micro quadcopters ($<\$20$) that require tracking speed of at least 30 frames per second, just to not get crashed in the wall. In order to compromise for the weak hardware, we suggest \emph{core-set} for pose-estimation or ICP. Such a coresets is a small scaled subset of the original $n$ tracked markers on the quadcopter, such that computing the orientation of the quadcopter using only the coreset, would give \emph{exactly} the same result as using the full set of $n$ markers. We prove that such a coreset of constant size (independent of $n$) always exists, and provide deterministic algorithm that computes it in $O(n)$ time. Our main tool is the Caratheodory Theorem. #R##N#By constructing the coreset on the cloud using one slow thread, and using the last computed coreset locally using a second parallel thread, we explain and show experimental results on how we turned a remote-controlled low-cost and safe toy quadcopter with no sensors, into an autonomous quadcopter. Source code for the benefit of the community and reproducing the results is available.

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)