Second-order orthant-based methods with enriched Hessian information for sparse \(\ell _1\) -optimization.
Juan Carlos de los ReyesE. LoayzaPedro MerinoPublished in: Comput. Optim. Appl. (2017)
Keyphrases
- optimization methods
- empirical studies
- significant improvement
- optimization problems
- neural network
- machine learning
- domain knowledge
- information sharing
- information sources
- sparse representation
- theoretical guarantees
- machine learning methods
- machine learning algorithms
- optimization algorithm
- information processing
- computational cost
- preprocessing
- website
- data mining