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: "statistical optimal transport posed as learning kernel embedding"
  Abstract: This work takes the novel approach of posing the statistical Optimal Transport (OT) problem as that of learning the transport plan's kernel mean embedding. The key advantage is that the estimates for the embeddings of the marginals can now be employed directly, leading to a dimension-free sample complexity for the proposed transport plan and transport map estimators. Also, because of the implicit smoothing in the kernel embeddings, the proposed estimators can perform out-of-sample estimation. Interestingly, the proposed formulation employs an MMD based regularization to avoid overfitting, which is complementary to existing $\phi$-divergence (entropy) based regularization techniques. An appropriate representer theorem is presented that leads to a fully kernelized formulation and hence the same formulation can be used to perform continuous/semi-discrete/discrete OT in any non-standard domain (as long as universal kernels in those domains are known). Finally, an ADMM based algorithm is presented for solving the kernelized formulation efficiently. Empirical results show that the proposed estimator outperforms discrete OT based estimator in terms of transport map accuracy.

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)