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 "infrastructure for usable machine learning the stanford dawn project"):
  Abstract: Despite incredible recent advances in machine learning, building machine learning applications remains prohibitively time-consuming and expensive for all but the best-trained, best-funded engineering organizations. This expense comes not from a need for new and improved statistical models but instead from a lack of systems and tools for supporting end-to-end machine learning application development, from data preparation and labeling to productionization and monitoring. In this document, we outline opportunities for infrastructure supporting usable, end-to-end machine learning applications in the context of the nascent DAWN (Data Analytics for What's Next) project at Stanford.

Includes members:
  Member "asap prioritizing attention via time series smoothing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "towards a near universal time series data mining tool introducing the matrix profile")
  Member "learning the structure of generative models without labeled data":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "flame a self adaptive auto labeling system for heterogeneous mobile processors")
  Member "noscope optimizing neural network queries over video at scale":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "video monitoring queries")
  Member "macrobase prioritizing attention in fast data":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "storyboard optimizing precomputed summaries for aggregation")
  Member "omnivore an optimizer for multi device deep learning on cpus and gpus":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "distributed learning of deep neural networks using independent subnet training")
  Member "socratic learning augmenting generative models to incorporate latent subsets in training data":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "zero shot task transfer")
  Member "a two pronged progress in structured dense matrix multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "learning fast algorithms for linear transforms using butterfly factorizations")
  Member "slimfast guaranteed results for data fusion and source reliability":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "goggles automatic training data generation with affinity coding")

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.LG(Machine Learning)