human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "intelligent real time mems sensor fusion and calibration"):
  Abstract: This paper discusses an innovative adaptive heterogeneous fusion algorithm based on the estimation of the mean square error of all variables used in real-time processing. The algorithm is designed for a fusion between derivative and absolute sensors and is explained by the fusion of the three-axial gyroscope, three-axial accelerometer, and three-axial magnetometer into attitude and heading estimation. Our algorithm has a similar error performance in the steady state but much faster dynamic response compared with the fixed-gain fusion algorithm. In comparison with the extended Kalman filter, the proposed algorithm converges faster and takes less computational time. On the other hand, Kalman filter has smaller mean square output error in a steady state but becomes unstable if the estimated state changes too rapidly. In addition, the noisy fusion deviation can be used in the process of calibration. This paper proposes and explains a real-time calibration method based on machine learning working in the online mode during run time. This allows compensation of sensor thermal drift right in the sensor's working environment without need of recalibration in the laboratory.

Includes members:
  Member "on calibration of three axis magnetometer":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "gyroscope calibration via magnetometer")
  Member "adam a method for stochastic optimization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")

Question: Please tell me which class the source paper 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)