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Increasing Convolutional Neural Networks Training Speed by Incremental Complexity Learning.

, and . BRACIS, page 103-108. IEEE Computer Society, (2018)

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Selective generation of training examples in active meta-learning., and . Int. J. Hybrid Intell. Syst., 5 (2): 59-70 (2008)Feature and algorithm selection with Hybrid Intelligent Techniques., , and . Int. J. Hybrid Intell. Syst., 8 (3): 115-116 (2011)Uncertainty Sampling-Based Active Selection of Datasetoids for Meta-learning., , and . ICANN (2), volume 6792 of Lecture Notes in Computer Science, page 454-461. Springer, (2011)Ensemble Methods for Label Noise Detection Under the Noisy at Random Model., , and . BRACIS, page 474-479. IEEE Computer Society, (2018)Automatic Information Extraction in Semi-structured Official Journals., , , , , and . SBRN, page 51-56. IEEE Computer Society, (2008)Active Learning to Support the Generation of Meta-examples., and . ICANN (1), volume 4668 of Lecture Notes in Computer Science, page 817-826. Springer, (2007)Selecting Machine Learning Algorithms Using the Ranking Meta-Learning Approach., , and . Meta-Learning in Computational Intelligence, volume 358 of Studies in Computational Intelligence, Springer, (2011)A hybrid particle swarm optimization and harmony search algorithm approach for multi-objective test case selection., , and . J. Braz. Comp. Soc., 21 (1): 19:1-19:20 (2015)Using Machine Learning Techniques to Combine Forecasting Methods., and . Australian Conference on Artificial Intelligence, volume 3339 of Lecture Notes in Computer Science, page 1122-1127. Springer, (2004)A Constrained Particle Swarm Optimization Approach for Test Case Selection., , and . SEKE, page 259-264. Knowledge Systems Institute Graduate School, (2010)