Improving the Accuracy in SpMV Implementation Selection with Machine Learning.
Reo FuruhataMinglu ZhaoMulya AgungRyusuke EgawaHiroyuki TakizawaPublished in: CANDAR (Workshops) (2020)
Keyphrases
- machine learning
- high accuracy
- pattern recognition
- high precision
- knowledge acquisition
- computational cost
- computational complexity
- detection rate
- feature selection
- selection algorithm
- database
- data mining
- correlation coefficient
- learning tasks
- highly accurate
- computational efficiency
- natural language processing
- prediction accuracy
- machine learning algorithms
- computer science
- database systems
- decision trees
- learning algorithm
- neural network