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 "a first look at deep learning apps on smartphones"):
  Abstract: We are in the dawn of deep learning explosion for smartphones. To bridge the gap between research and practice, we present the first empirical study on 16,500 the most popular Android apps, demystifying how smartphone apps exploit deep learning in the wild. To this end, we build a new static tool that dissects apps and analyzes their deep learning functions. Our study answers threefold questions: what are the early adopter apps of deep learning, what do they use deep learning for, and how do their deep learning models look like. Our study has strong implications for app developers, smartphone vendors, and deep learning R\&D. On one hand, our findings paint a promising picture of deep learning for smartphones, showing the prosperity of mobile deep learning frameworks as well as the prosperity of apps building their cores atop deep learning. On the other hand, our findings urge optimizations on deep learning models deployed on smartphones, the protection of these models, and validation of research ideas on these models.

Includes members:
  Member "pcamp performance comparison of machine learning packages on the edges":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "edge intelligence paving the last mile of artificial intelligence with edge computing")
  Member "deepcache principled cache for mobile deep vision":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "patdnn achieving real time dnn execution on mobile devices with pattern based weight pruning")
  Member "digital watermarking for deep neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "entangled watermarks as a defense against model extraction")
  Member "mlcapsule guarded offline deployment of machine learning as a service":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "survey of attacks and defenses on edge deployed neural networks")
  Member "turning your weakness into a strength watermarking deep neural networks by backdooring":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "entangled watermarks as a defense against model extraction")
  Member "deepsigns a generic watermarking framework for ip protection of deep learning models":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "survey of attacks and defenses on edge deployed neural networks")
  Member "securing input data of deep learning inference systems via partitioned enclave execution":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "industrial scale privacy preserving deep neural network")
  Member "understanding diverse usage patterns from large scale appstore service profiles":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "an empirical study of blockchain based decentralized applications")

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)