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 "stratum a serverless framework for lifecycle management of machine learning based data analytics tasks"):
  Abstract: With the proliferation of machine learning (ML) libraries and frameworks, and the programming languages that they use, along with operations of data loading, transformation, preparation and mining, ML model development is becoming a daunting task. Furthermore, with a plethora of cloud-based ML model development platforms, heterogeneity in hardware, increased focus on exploiting edge computing resources for low-latency prediction serving and often a lack of a complete understanding of resources required to execute ML workflows efficiently, ML model deployment demands expertise for managing the lifecycle of ML workflows efficiently and with minimal cost. To address these challenges, we propose an end-to-end data analytics, a serverless platform called Stratum. Stratum can deploy, schedule and dynamically manage data ingestion tools, live streaming apps, batch analytics tools, ML-as-a-service (for inference jobs), and visualization tools across the cloud-fog-edge spectrum. This paper describes the Stratum architecture highlighting the problems it resolves.

Includes members:
  Member "slaq quality driven scheduling for distributed machine learning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hypersched dynamic resource reallocation for model development on a deadline")
  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")

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.SE(Software Engineering)