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 "non unique games over compact groups and orientation estimation in cryo em"):
  Abstract: Let $\mathcal{G}$ be a compact group and let $f_{ij} \in L^2(\mathcal{G})$. We define the Non-Unique Games (NUG) problem as finding $g_1,\dots,g_n \in \mathcal{G}$ to minimize $\sum_{i,j=1}^n f_{ij} \left( g_i g_j^{-1}\right)$. We devise a relaxation of the NUG problem to a semidefinite program (SDP) by taking the Fourier transform of $f_{ij}$ over $\mathcal{G}$, which can then be solved efficiently. The NUG framework can be seen as a generalization of the little Grothendieck problem over the orthogonal group and the Unique Games problem and includes many practically relevant problems, such as the maximum likelihood estimator} to registering bandlimited functions over the unit sphere in $d$-dimensions and orientation estimation in cryo-Electron Microscopy.

Includes members:
  Member "synchronization over z2 and community detection in signed multiplex networks with constraints":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the noise sensitivity phase transition in spectral group synchronization over compact groups")
  Member "near optimal joint object matching via convex relaxation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "rgb d individual segmentation")
  Member "fast steerable principal component analysis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "single particle cryo electron microscopy mathematical theory computational challenges and opportunities")
  Member "decoding binary node labels from censored edge measurements phase transition and efficient recovery":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "spectral clustering of signed graphs via matrix power means")
  Member "exact recovery in the stochastic block model":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "renyi entropy bounds on the active learning cost performance tradeoff")
  Member "multireference alignment using semidefinite programming":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "synchronisation of partial multi matchings via non negative factorisations")
  Member "approximating the little grothendieck problem over the orthogonal and unitary groups":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "multi frequency phase synchronization")
  Member "efficient rounding for the noncommutative grothendieck inequality":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "an overview of robust subspace 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.CV(Computer Vision and Pattern Recognition)