Enabling One-Size-Fits-All Compilation Optimization for Inference Across Machine Learning Computers.
Yuanbo WenQi GuoZidong DuJianxing XuZhenxing ZhangXing HuWei LiRui ZhangChao WangXuehai ZhouTianshi ChenPublished in: IEEE Trans. Computers (2022)
Keyphrases
- machine learning
- optimization algorithm
- global optimization
- computer systems
- optimization process
- feature selection
- machine learning methods
- dual decomposition
- optimization problems
- inductive learning
- bayesian networks
- statistical learning
- bayesian inference
- personal computer
- optimization methods
- constrained optimization
- machine learning approaches
- optimization method
- optimization approaches
- learning systems
- active learning
- learning algorithm
- decision trees
- information extraction
- knowledge acquisition
- computer science
- semi supervised learning
- data mining
- knowledge compilation
- statistical inference
- dynamic bayesian networks
- optimization model
- explanation based learning
- reinforcement learning
- computational complexity
- data analysis
- model selection
- knowledge discovery
- computer technology
- genetic algorithm
- computational intelligence
- graphical models
- combinatorial optimization
- text classification