Convergence conditions and numerical comparison of global optimization methods based on dimensionality reduction schemes.
Vladimir A. GrishaginRuslan IsrafilovYaroslav D. SergeyevPublished in: Appl. Math. Comput. (2018)
Keyphrases
- optimization methods
- global convergence
- dimensionality reduction
- quasi newton
- optimization method
- optimization problems
- simulated annealing
- convergence analysis
- particle swarm
- feature extraction
- unconstrained optimization
- stochastic methods
- efficient optimization
- optimization approaches
- continuous optimization
- initial conditions
- pattern recognition
- sensitivity analysis
- direct optimization
- trust region
- gradient method
- stopping criteria
- line search
- high dimensional
- principal component analysis
- bayesian network models
- high dimensional data
- feature space
- evolution strategy
- data representation
- feature selection
- convergence rate
- high dimensionality
- number of iterations required