human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "manopt a matlab toolbox for optimization on manifolds"
  Abstract: Optimization on manifolds is a rapidly developing branch of nonlinear optimization. Its focus is on problems where the smooth geometry of the search space can be leveraged to design efficient numerical algorithms. In particular, optimization on manifolds is well-suited to deal with rank and orthogonality constraints. Such structured constraints appear pervasively in machine learning applications, including low-rank matrix completion, sensor network localization, camera network registration, independent component analysis, metric learning, dimensionality reduction and so on. The Manopt toolbox, available at www.manopt.org, is a user-friendly, documented piece of software dedicated to simplify experimenting with state of the art Riemannian optimization algorithms. We aim particularly at reaching practitioners outside our field.

Connected through hyperedge HE-1 (induced by source paper "joint constellation design for the two user non coherent multiple access channel"):
  with members:
    - "cube split a structured grassmannian constellation for non coherent simo communications"
    - "the optimal dof region for the two user non coherent simo multiple access channel"
    - "energy based modulation for noncoherent massive simo systems"

Connected through hyperedge HE-2 (induced by source paper "discriminative video representation learning using support vector classifiers"):
  with members:
    - "moments in time dataset one million videos for event understanding"
    - "a short note about kinetics 600"
    - "non linear temporal subspace representations for activity recognition"
    - "video representation learning using discriminative pooling"
    - "higher order pooling of cnn features via kernel linearization for action recognition"
    - "quo vadis action recognition a new model and the kinetics dataset"
    - "generalized rank pooling for activity recognition"
    - "appearance and relation networks for video classification"

Connected through hyperedge HE-3 (induced by source paper "sliced wasserstein generative models"):
  with members:
    - "video to video synthesis"
    - "improving the improved training of wasserstein gans a consistency term and its dual effect"
    - "spectral normalization for generative adversarial networks"
    - "improving gans using optimal transport"
    - "banach wasserstein gan"
    - "generative modeling using the sliced wasserstein distance"
    - "began boundary equilibrium generative adversarial networks"
    - "gans trained by a two time scale update rule converge to a nash equilibrium"

Connected through hyperedge HE-4 (induced by source paper "joint representation of multiple geometric priors via a shape decomposition model for single monocular 3d pose estimation"):
  with members:
    - "3d human pose machines with self supervised learning"
    - "ordinal depth supervision for 3d human pose estimation"
    - "monocap monocular human motion capture using a cnn coupled with a geometric prior"
    - "sparse representation for 3d shape estimation a convex relaxation approach"
    - "towards 3d human pose estimation in the wild a weakly supervised approach"
    - "lifting from the deep convolutional 3d pose estimation from a single image"
    - "a simple yet effective baseline for 3d human pose estimation"
    - "learning from synthetic humans"

Connected through hyperedge HE-5 (induced by source paper "a probabilistic approach for learning embeddings without supervision"):
  with members:
    - "crdoco pixel level domain transfer with cross domain consistency"
    - "hardness aware deep metric learning"
    - "few shot learning with localization in realistic settings"
    - "unsupervised embedding learning via invariant and spreading instance feature"
    - "generalized zero and few shot learning via aligned variational autoencoders"
    - "deep clustering for unsupervised learning of visual features"
    - "adversarial metric learning"
    - "mining on manifolds metric learning without labels"

Connected through hyperedge HE-6 (induced by source paper "probabilistic permutation synchronization using the riemannian structure of the birkhoff polytope"):
  with members:
    - "synchronisation of partial multi matchings via non negative factorisations"
    - "ppfnet global context aware local features for robust 3d point matching"
    - "bayesian pose graph optimization via bingham distributions and tempered geodesic mcmc"
    - "averaging stochastic gradient descent on riemannian manifolds"
    - "orb slam2 an open source slam system for monocular stereo and rgb d cameras"
    - "cad priors for accurate and flexible instance reconstruction"
    - "consistent multiple graph matching with multi layer random walks synchronization"
    - "multi image semantic matching by mining consistent features"

Connected through hyperedge HE-7 (induced by source paper "fitting comparison and alignment of trajectories on positive semi definite matrices with application to action recognition"):
  with members:
    - "uav gesture a dataset for uav control and gesture recognition"
    - "openpose realtime multi person 2d pose estimation using part affinity fields"
    - "human action recognition and prediction a survey"
    - "deep covariance descriptors for facial expression recognition"
    - "spatial temporal graph convolutional networks for skeleton based action recognition"
    - "optimized skeleton based action recognition via sparsified graph regression"
    - "a novel geometric framework on gram matrix trajectories for human behavior understanding"
    - "automatic analysis of facial expressions based on deep covariance trajectories"

Connected through hyperedge HE-8 (induced by source paper "robust hybrid precoding for beam misalignment in millimeter wave communications"):
  with members:
    - "secure hybrid analog and digital receive beamforming schemes for efficient interference reduction"
    - "impact of beam misalignment on hybrid beamforming noma for mmwave communications"
    - "joint power allocation and beamforming for non orthogonal multiple access noma in 5g millimeter wave communications"
    - "alternating minimization for hybrid precoding in multiuser ofdm mmwave systems"
    - "alternating minimization algorithms for hybrid precoding in millimeter wave mimo systems"
    - "analysis on 60 ghz wireless communications with beamwidth dependent misalignment"
    - "hybrid digital and analog beamforming design for large scale antenna arrays"
    - "massive mimo combining with switches"

Question: Please tell me which class the center node 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.MS(Mathematical Software)