Convergence of successive linear programming algorithms for noisy functions.
Christoph HansknechtChristian KirchesPaul MannsPublished in: Comput. Optim. Appl. (2024)
Keyphrases
- linear programming
- orders of magnitude
- theoretical analysis
- learning algorithm
- interior point
- times faster
- convergence property
- machine learning
- convergence rate
- computationally efficient
- np hard
- data structure
- data mining techniques
- image restoration
- benchmark datasets
- upper bound
- differential evolution
- computational cost
- combinatorial optimization
- recently developed
- incomplete data
- global convergence
- significant improvement