Optimizing Deep Learning Inference on Embedded Systems Through Adaptive Model Selection.
Vicent Sanz MarcoBen TaylorZheng WangYehia ElkhatibPublished in: ACM Trans. Embed. Comput. Syst. (2020)
Keyphrases
- model selection
- embedded systems
- deep learning
- unsupervised learning
- machine learning
- statistical inference
- cross validation
- low cost
- hyperparameters
- parameter estimation
- mixture model
- bayesian model selection
- bayesian networks
- feature selection
- probabilistic inference
- gaussian process
- software systems
- selection criterion
- model selection criteria
- bayesian inference
- mental models
- weakly supervised
- expectation maximization
- computer vision
- information criterion
- artificial intelligence