On the choice of the low-dimensional domain for global optimization via random embeddings.
Mickaël BinoisDavid GinsbourgerOlivier RoustantPublished in: J. Glob. Optim. (2020)
Keyphrases
- global optimization
- low dimensional
- high dimensional
- dimensionality reduction
- manifold learning
- ant colony algorithm
- principal component analysis
- particle swarm optimization
- euclidean space
- high dimensional data
- data points
- vector space
- input space
- global solution
- feature space
- evolutionary programming
- global optima
- pso algorithm
- deterministic annealing
- inverse problems
- low dimensional spaces
- search capabilities
- global search
- particle swarm optimisation
- neural network
- binary particle swarm optimization