On the Convergence of Prior-Guided Zeroth-Order Optimization Algorithms.
Shuyu ChengGuoqiang WuJun ZhuPublished in: CoRR (2021)
Keyphrases
- optimization problems
- discrete optimization
- learning algorithm
- combinatorial optimization
- orders of magnitude
- benchmark datasets
- significant improvement
- quasi newton
- optimization approaches
- convergence analysis
- convergence rate
- computational cost
- computationally efficient
- theoretical justification
- feature selection
- global convergence
- optimization procedure
- approximately optimal
- efficient optimization
- bayesian methods
- optimization methods
- data structure
- machine learning
- search algorithm
- machine learning algorithms
- prior knowledge
- worst case