An Empirical Evaluation of Mutation Operators for Deep Learning Systems.
Gunel JahangirovaPaolo TonellaPublished in: ICST (2020)
Keyphrases
- learning systems
- mutation operator
- evolutionary algorithm
- differential evolution
- genetic algorithm
- crossover operator
- learning environment
- convergence rate
- machine learning
- learning resources
- learning materials
- computer supported
- multi objective
- genetic operators
- learning process
- nsga ii
- crossover and mutation
- fitness function
- step size
- evolutionary computation
- learning styles
- crossover and mutation operators
- technology enhanced learning systems
- neural network
- multi objective optimization
- genetic programming
- optimization problems
- objective function
- optimal parameter settings
- branch and bound
- genetic algorithm ga
- multimedia
- human learning
- learning algorithm