Corpus ID: 58028834

NeuNetS: An Automated Synthesis Engine for Neural Network Design

@article{Sood2019NeuNetSAA,
  title={NeuNetS: An Automated Synthesis Engine for Neural Network Design},
  author={Atin Sood and Benjamin Elder and Benjamin Herta and Chao Xue and Constantine Bekas and Adelmo Cristiano Innocenza Malossi and Debashish Saha and Florian Scheidegger and Ganesh Venkataraman and Gegi Thomas and Giovanni Mariani and Hendrik Strobelt and Horst Samulowitz and Martin Wistuba and Matteo Manica and Mihir R. Choudhury and Rong Yan and Roxana Istrate and Ruchir Puri and Tejaswini Pedapati},
  journal={ArXiv},
  year={2019},
  volume={abs/1901.06261}
}
  • Atin Sood, Benjamin Elder, +17 authors Tejaswini Pedapati
  • Published in ArXiv 2019
  • Mathematics, Computer Science
  • Application of neural networks to a vast variety of practical applications is transforming the way AI is applied in practice. Pre-trained neural network models available through APIs or capability to custom train pre-built neural network architectures with customer data has made the consumption of AI by developers much simpler and resulted in broad adoption of these complex AI models. While prebuilt network models exist for certain scenarios, to try and meet the constraints that are unique to… CONTINUE READING

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