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 "optical reservoir computing using multiple light scattering for chaotic systems prediction"):
  Abstract: Reservoir Computing is a relatively recent computational framework based on a large Recurrent Neural Network with fixed weights. Many physical implementations of Reservoir Computing have been proposed to improve speed and energy efficiency. In this study, we report new advances in Optical Reservoir Computing using multiple light scattering to accelerate the recursive computation of the reservoir states. Two different spatial light modulation technologies, namely, phase or binary amplitude modulations, are compared. Phase modulation is a promising direction already employed in other photonic implementations of Reservoir Computing. Additionally, we report a Digital-Micromirror-based Reservoir Computing at up to 640 Hz, more than double the previously reported frequency using a remotely controlled optical device developed by LightOn, and present new binarization strategies to improve the performance of binarized Reservoir Computing.

Includes members:
  Member "recent advances in physical reservoir computing a review":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "advectivenet an eulerian lagrangian fluidic reservoir for point cloud processing")
  Member "a substrate independent framework to characterise reservoir computers":
    also connected through other hyperedges:
      (none)
  Member "echo state networks are universal":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "recent advances in physical reservoir computing a review")
  Member "scaling up echo state networks with multiple light scattering":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "recent advances in physical reservoir computing a review")
  Member "reinforcement learning in a large scale photonic recurrent neural network":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "analysis of diffractive optical neural networks and their integration with electronic neural networks")
  Member "newma a new method for scalable model free online change point detection":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "kernel computations from large scale random features obtained by optical processing units")
  Member "using a reservoir computer to learn chaotic attractors with applications to chaos synchronization and cryptography":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "data driven reconstruction of nonlinear dynamics from sparse observation")
  Member "hardware for machine learning challenges and opportunities":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "fpga based accelerators of deep learning networks for learning and classification a review")

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.ET(Emerging Technologies)