Adaptive algorithm selection method (AASM) for dynamic software tuning.
Kuniyasu SuzakiTakio KuritaHitoshi TanumaSatoshi HiranoPublished in: COMPSAC (1993)
Keyphrases
- high accuracy
- improved algorithm
- objective function
- selection algorithm
- cost function
- experimental evaluation
- computational cost
- synthetic and real images
- detection method
- theoretical analysis
- significant improvement
- optimization algorithm
- dynamic programming
- preprocessing
- computational complexity
- k means
- clustering method
- fine tuning
- input data
- segmentation algorithm
- single pass
- detection algorithm
- prior information
- recognition algorithm
- experimental study
- decomposition method
- optimization method
- classification algorithm
- classification method
- estimation algorithm
- node selection
- recursive least squares
- adaptive threshold
- learning algorithm
- computationally efficient
- filtering algorithm
- matching algorithm
- segmentation method
- computational efficiency
- region of interest
- np hard
- probabilistic model
- high efficiency
- tree structure
- search space
- parameter tuning
- particle swarm optimization
- parameter settings
- em algorithm
- optimal solution
- similarity measure
- neural network
- multi objective
- reconstruction method
- selection strategy
- simulated annealing
- expectation maximization
- kalman filter
- mathematical model