Two computationally efficient polynomial-iteration infeasible interior-point algorithms for linear programming.
Yaguang YangPublished in: Numer. Algorithms (2018)
Keyphrases
- computationally efficient
- linear programming
- recently developed
- computational complexity
- optimization problems
- neural network
- learning algorithm
- objective function
- primal dual
- computationally expensive
- interior point
- linear program
- higher order
- orders of magnitude
- machine learning algorithms
- markov random field
- convergence rate
- constraint propagation
- computational cost
- machine learning