Review of "Experimental Methods for the Analysis of Optimization Algorithms", Thomas Bartz-Beielstein, Marco Chiarandini, Luı's Paquete, Mike Preuss. Springer, 2010.
Rubén RuizPublished in: Eur. J. Oper. Res. (2011)
Keyphrases
- optimization methods
- computational cost
- optimization problems
- computationally expensive
- methods outperform
- efficient optimization
- significant improvement
- complexity analysis
- benchmark datasets
- machine learning methods
- monte carlo methods
- evaluation measures
- high computational complexity
- problems in computer vision
- real world
- machine learning algorithms
- search methods
- computationally intensive
- computer vision algorithms
- qualitative and quantitative
- synthetic and real datasets
- data analysis
- discrete optimization
- learning algorithm
- convex optimization problems
- clustering algorithm
- optimization approaches
- methods can be applied
- stochastic gradient
- search algorithm
- methods require
- algorithms require
- optimization algorithm