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 "new algorithms and improved guarantees for one bit compressed sensing on manifolds"):
  Abstract: We study the problem of approximately recovering signals on a manifold from one-bit linear measurements drawn from either a Gaussian ensemble, partial circulant ensemble, or bounded orthonormal ensemble and quantized using Sigma-Delta or distributed noise shaping schemes. We assume we are given a Geometric Multi-Resolution Analysis, which approximates the manifold, and we propose a convex optimization algorithm for signal recovery. We prove an upper bound on the recovery error which outperforms prior works that use memoryless scalar quantization, requires a simpler analysis, and extends the class of measurements beyond Gaussians. Finally, we illustrate our results with numerical experiments.

Includes members:
  Member "fast binary embeddings and quantized compressed sensing with structured matrices":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "adapted decimation on finite frames for arbitrary orders of sigma delta quantization")
  Member "on recovery guarantees for one bit compressed sensing on manifolds":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "quantized compressed sensing by rectified linear units")
  Member "quantization for low rank matrix recovery":
    also connected through other hyperedges:
      (none)
  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-3 (induced by source paper "adapted decimation on finite frames for arbitrary orders of sigma delta quantization")
  Member "from compressed sensing to compressed bit streams practical encoders tractable decoders":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "sub gaussian matrices on sets optimal tail dependence and applications")
  Member "quantization and compressive sensing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "serial quantization for sparse time sequences")
  Member "approximation of points on low dimensional manifolds via random linear projections":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "restricted isometry property of subspace projection matrix under random compression")
  Member "one bit compressed sensing by linear programming":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "efficient active learning of sparse halfspaces with arbitrary bounded noise")

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)