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 "contextual stochastic block models"):
  Abstract: We provide the first information theoretic tight analysis for inference of latent community structure given a sparse graph along with high dimensional node covariates, correlated with the same latent communities. Our work bridges recent theoretical breakthroughs in the detection of latent community structure without nodes covariates and a large body of empirical work using diverse heuristics for combining node covariates with graphs for inference. The tightness of our analysis implies in particular, the information theoretical necessity of combining the different sources of information. Our analysis holds for networks of large degrees as well as for a Gaussian version of the model.

Includes members:
  Member "algorithmic decision making and the cost of fairness":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "algorithmic fairness")
  Member "clustering attributed graphs models measures and methods":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "community detection in node attributed social networks a survey")
  Member "phase transitions in semisupervised clustering of sparse networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "renyi entropy bounds on the active learning cost performance tradeoff")
  Member "statistical estimation from denoising to sparse regression and hidden cliques":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "precise error analysis of regularized m estimators in high dimensions")
  Member "partitioning networks with node attributes by compressing information flow":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "an enhanced multi objective biogeography based optimization algorithm for automatic detection of overlapping communities in a social network with node attributes")
  Member "community detection in networks with node attributes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "finding temporal patterns using algebraic fingerprints")
  Member "mining attribute structure correlated patterns in large attributed graphs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "detection of community structures in networks with nodal features based on generative probabilistic approach")
  Member "latent multi group membership graph model":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "struct mmsb mixed membership stochastic blockmodels with interpretable structured priors")

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.SI(Social and Information Networks)