9 citations · 9 across the 1 of their papers we have counts for
3 papers
LNAS: Learning to Optimize Neural Architectures via Continuous-Action Reinforcement Learning
Keith G. Mills, Fred X. Han, Mohammad Salameh +6
Neural architecture search (NAS) has achieved remarkable results in deep neural network design. Differentiable architecture search converts the search over discrete architectures i…
Generative Adversarial Neural Architecture Search
Seyed Saeed Changiz Rezaei, Fred X. Han, Di Niu +5
Despite the empirical success of neural architecture search (NAS) in deep learning applications, the optimality, reproducibility and cost of NAS schemes remain hard to assess. In t…
Neural Architecture Search For Keyword Spotting
Tong Mo, Yakun Yu, Mohammad Salameh +2
Deep neural networks have recently become a popular solution to keyword spotting systems, which enable the control of smart devices via voice. In this paper, we apply neural archit…