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 "packaging and sharing machine learning models via the acumos ai open platform"):
  Abstract: Applying Machine Learning (ML) to business applications for automation usually faces difficulties when integrating diverse ML dependencies and services, mainly because of the lack of a common ML framework. In most cases, the ML models are developed for applications which are targeted for specific business domain use cases, leading to duplicated effort, and making reuse impossible. This paper presents Acumos, an open platform capable of packaging ML models into portable containerized microservices which can be easily shared via the platform's catalog, and can be integrated into various business applications. We present a case study of packaging sentiment analysis and classification ML models via the Acumos platform, permitting easy sharing with others. We demonstrate that the Acumos platform reduces the technical burden on application developers when applying machine learning models to their business applications. Furthermore, the platform allows the reuse of readily available ML microservices in various business domains.

Includes members:
  Member "tensorflow serving flexible high performance ml serving":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "aibench an agile domain specific benchmarking methodology and an ai benchmark suite")
  Member "clipper a low latency online prediction serving system":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "train large then compress rethinking model size for efficient training and inference of transformers")
  Member "hyperface a deep multi task learning framework for face detection landmark localization pose estimation and gender recognition":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "two stream aural visual affect analysis in the wild")
  Member "google s neural machine translation system bridging the gap between human and machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "automl zero evolving machine learning algorithms from scratch")
  Member "tensorflow a system for large scale machine learning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")
  Member "deep learning in neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "π nets deep polynomial neural networks")
  Member "learning transferable features with deep adaptation networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a survey on contextual embeddings")
  Member "mllib machine learning in apache spark":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "multi layer optimizations for end to end data analytics")

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.AI(Artificial Intelligence)