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 "blind demixing for low latency communication"):
  Abstract: In the next generation wireless networks, lowlatency communication is critical to support emerging diversified applications, e.g., Tactile Internet and Virtual Reality. In this paper, a novel blind demixing approach is developed to reduce the channel signaling overhead, thereby supporting low-latency communication. Specifically, we develop a low-rank approach to recover the original information only based on a single observed vector without any channel estimation. Unfortunately, this problem turns out to be a highly intractable non-convex optimization problem due to the multiple non-convex rankone constraints. To address the unique challenges, the quotient manifold geometry of product of complex asymmetric rankone matrices is exploited by equivalently reformulating original complex asymmetric matrices to the Hermitian positive semidefinite matrices. We further generalize the geometric concepts of the complex product manifolds via element-wise extension of the geometric concepts of the individual manifolds. A scalable Riemannian trust-region algorithm is then developed to solve the blind demixing problem efficiently with fast convergence rates and low iteration cost. Numerical results will demonstrate the algorithmic advantages and admirable performance of the proposed algorithm compared with the state-of-art methods.

Includes members:
  Member "nonconvex demixing from bilinear measurements":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "learning one hidden layer neural networks via provable gradient descent with random initialization")
  Member "regularized gradient descent a nonconvex recipe for fast joint blind deconvolution and demixing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "blind over the air computation and data fusion via provable wirtinger flow")
  Member "painless breakups efficient demixing of low rank matrices":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "heterogeneous multireference alignment a single pass approach")
  Member "blind deconvolution by a steepest descent algorithm on a quotient manifold":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "phase retrieval of low rank matrices by anchored regression")
  Member "a survey on low latency towards 5g ran core network and caching solutions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the design of dynamic probabilistic caching with time varying content popularity")
  Member "no spurious local minima in nonconvex low rank problems a unified geometric analysis":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "no spurious local minima in deep quadratic networks")
  Member "low rank matrix completion for topological interference management by riemannian pursuit":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "low rank matrix completion a contemporary survey")
  Member "blind deconvolution meets blind demixing algorithms and performance bounds":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "support recovery for sparse signals with unknown non stationary modulation")

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)