A superlinearly convergent norm-relaxed method of quasi-strongly sub-feasible direction for inequality constrained minimax problems.
Jin-bao JianJie LiHai-Yan ZhengJian-Ling LiPublished in: Appl. Math. Comput. (2014)
Keyphrases
- preprocessing
- detection method
- computational cost
- combinatorial optimization
- significant improvement
- high precision
- cost function
- segmentation method
- learning algorithm
- high accuracy
- model selection
- probabilistic model
- alternative methods
- search methods
- synthetic data
- clustering method
- optimization problems
- experimental evaluation
- dynamic programming
- lower bound
- optimal solution
- multiscale
- similarity measure