Using matrix approximation for high-dimensional discrete optimization problems: Server consolidation based on cyclic time-series data.
Thomas SetzerMartin BichlerPublished in: Eur. J. Oper. Res. (2013)
Keyphrases
- high dimensional
- discrete optimization problems
- matrix approximation
- traveling salesman problem
- discrete optimization
- least squares
- optimization problems
- approximation error
- low dimensional
- decision problems
- data points
- branch and bound method
- theoretical guarantees
- maximum entropy
- high dimensional data
- dimensionality reduction
- swarm intelligence
- similarity search
- nearest neighbor
- kernel function
- bregman divergences
- feature space
- low rank matrix approximation
- combinatorial optimization problems
- low rank matrix
- gene expression data
- combinatorial optimization
- learning algorithm
- ant colony optimization
- evolutionary algorithm
- linear combination
- sufficient conditions