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 "adapted decimation on finite frames for arbitrary orders of sigma delta quantization"):
  Abstract: In Analog-to-digital (A/D) conversion, signal decimation has been proven to greatly improve the efficiency of data storage while maintaining high accuracy. When one couples signal decimation with the $\Sigma\Delta$ quantization scheme, the reconstruction error decays exponentially with respect to the bit-rate. We build on our previous result, which extends signal decimation to finite frames, albeit only up to the second order. In this study, we introduce a new scheme called adapted decimation, which yields polynomial reconstruction error decay rate of arbitrary order with respect to the oversampling rate, and exponential with respect to the bit-rate.

Includes members:
  Member "analysis of decimation on finite frames with sigma delta quantization":
    also connected through other hyperedges:
      (none)
  Member "fast binary embeddings and quantized compressed sensing with structured matrices":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "new algorithms and improved guarantees for one bit compressed sensing on manifolds")
  Member "distributed noise shaping quantization i beta duals of finite frames and near optimal quantization of random measurements":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "new algorithms and improved guarantees for one bit compressed sensing on manifolds")
  Member "exact reconstruction of signals in evolutionary systems via spatiotemporal trade off":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "analysis of decimation on finite frames with sigma delta quantization")
  Member "a deterministic analysis of decimation for sigma delta quantization of bandlimited functions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "analysis of decimation on finite frames with sigma delta quantization")
  Member "noise shaping quantization methods for frame based and compressive sampling systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "high performance quantization for spectral super resolution")
  Member "near optimal encoding for sigma delta quantization of finite frame expansions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "quantization for low rank matrix recovery")

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.IT(Information Theory)