Quality-Diversity Algorithms Can Provably Be Helpful for Optimization.
Chao QianKe XueRen-Jian WangPublished in: CoRR (2024)
Keyphrases
- optimization problems
- orders of magnitude
- discrete optimization
- learning algorithm
- recently developed
- optimization algorithm
- machine learning
- quality measures
- optimization methods
- times faster
- theoretical analysis
- evolutionary algorithm
- lower bound
- genetic algorithm
- data sets
- computationally efficient
- worst case
- benchmark datasets
- computational complexity
- image processing
- stochastic search
- stochastic gradient
- convex optimization problems