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 "slimfast guaranteed results for data fusion and source reliability"):
  Abstract: We focus on data fusion, i.e., the problem of unifying conflicting data from data sources into a single representation by estimating the source accuracies. We propose SLiMFast, a framework that expresses data fusion as a statistical learning problem over discriminative probabilistic models, which in many cases correspond to logistic regression. In contrast to previous approaches that use complex generative models, discriminative models make fewer distributional assumptions over data sources and allow us to obtain rigorous theoretical guarantees. Furthermore, we show how SLiMFast enables incorporating domain knowledge into data fusion, yielding accuracy improvements of up to 50\% over state-of-the-art baselines. Building upon our theoretical results, we design an optimizer that obviates the need for users to manually select an algorithm for learning SLiMFast's parameters. We validate our optimizer on multiple real-world datasets and show that it can accurately predict the learning algorithm that yields the best data fusion results.

Includes members:
  Member "from data fusion to knowledge fusion":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "knowledge federation hierarchy and unification")
  Member "incremental knowledge base construction using deepdive":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "joint reasoning for multi faceted commonsense knowledge")
  Member "a survey on truth discovery":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "joint inference on truth rumor and their sources in social networks")
  Member "knowledge based trust estimating the trustworthiness of web sources":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "detecting toxicity in news articles application to bulgarian")
  Member "comprehensive and reliable crowd assessment algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "metrology for ai from benchmarks to instruments")
  Member "global convergence of stochastic gradient descent for some non convex matrix problems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "distributed stochastic algorithms for high rate streaming principal component analysis")
  Member "dimmwitted a study of main memory statistical analytics":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "distributed learning of deep neural networks using independent subnet training")
  Member "a bayesian approach to discovering truth from conflicting sources for data integration":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "open knowledge enrichment for long tail entities")

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.DB(Databases)