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: "approximate query service on autonomous iot cameras"
  Abstract: Today's analytics-powered cameras are still limited to urban, residential areas where power/network resources abound. To expand them to more diverse environments, especially those are off-grid and highly network-constrained, the cameras shall be ``autonomous'', i.e., independent from external power supply and compute infrastructure. Can autonomous cameras do any useful analytics? Our response is iCam, a runtime for autonomous cameras, that is capable of producing useful analytics results with frugal camera resources. iCam is built atop two novel techniques: (1) For the first time, iCam explores the joint tradeoff from both sampling strategy and wide selection of NN choices, and unifies the errors from both sources into one single bounded error. (2) Observing the disparate video characteristics across different time windows, iCam employs a learning-based planner that judiciously decides the sampling action at runtime. We test iCam with more than 1,000 hours of videos. On typical embedded hardware, iCam continuously generates object counts that are only within 11% of the true counts. Alongside the counts, iCam presents narrow error estimation which are shown to be bounded. It achieves up to 3.4x smaller bounded error over baselines.

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.DB(Databases)