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: "the infinite hierarchical factor regression model"
  Abstract: We propose a nonparametric Bayesian factor regression model that accounts for uncertainty in the number of factors, and the relationship between factors. To accomplish this, we propose a sparse variant of the Indian Buffet Process and couple this with a hierarchical model over factors, based on Kingman's coalescent. We apply this model to two problems (factor analysis and factor regression) in gene-expression data analysis.

Connected through hyperedge HE-1 (induced by source paper "a computational model of commonsense moral decision making"):
  with members:
    - "a voting based system for ethical decision making"
    - "the social dilemma of autonomous vehicles"
    - "one shot learning with memory augmented neural networks"
    - "rationalizing neural predictions"
    - "matching networks for one shot learning"
    - "wavenet a generative model for raw audio"
    - "google s neural machine translation system bridging the gap between human and machine translation"
    - "going deeper with convolutions"

Connected through hyperedge HE-2 (induced by source paper "collapsed variational inference for nonparametric bayesian group factor analysis"):
  with members:
    - "sparse group factor analysis for biclustering of multiple data sources"
    - "stochastic collapsed variational bayesian inference for latent dirichlet allocation"
    - "a slice sampler for restricted hierarchical beta process with applications to shared subspace learning"

Connected through hyperedge HE-3 (induced by source paper "correlated non parametric latent feature models"):
  with members:
    - "the phylogenetic indian buffet process a non exchangeable nonparametric prior for latent features"
    - "nonparametric bayes pachinko allocation"

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.LG(Machine Learning)