A Probabilistic Machine Learning Approach to Scheduling Parallel Loops with Bayesian Optimization.
Kyurae KimYoungjae KimSungyong ParkPublished in: CoRR (2022)
Keyphrases
- machine learning
- bayesian networks
- posterior probability
- scheduling problem
- optimization algorithm
- parallel machines
- scheduling algorithm
- knowledge acquisition
- optimization problems
- parallel processors
- global optimization
- vehicle routing
- prior probabilities
- data driven
- pattern recognition
- efficient optimization
- multiprocessor systems
- data mining
- machine learning methods
- decision theory
- optimization approaches
- identical machines
- covariate shift
- machine learning algorithms
- knowledge representation
- support vector machine
- learning tasks
- computer architecture
- learning algorithm
- feature selection
- decision trees
- reinforcement learning
- probability distribution
- information extraction
- probability theory
- natural language processing
- text classification
- resource constraints
- optimization process
- uncertain data
- resource allocation