2018
DOI: 10.1109/access.2018.2831079
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Processor Design Space Exploration via Statistical Sampling and Semi-Supervised Ensemble Learning

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Cited by 13 publications
(2 citation statements)
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“…Third, ANN is more accurate than the decision tree, but it is less accurate than LEAPER. This is because ANN requires a much larger training dataset to reach LEAPER 's accuracy [65].…”
Section: Base Model Accuracy Analysismentioning
confidence: 99%
“…Third, ANN is more accurate than the decision tree, but it is less accurate than LEAPER. This is because ANN requires a much larger training dataset to reach LEAPER 's accuracy [65].…”
Section: Base Model Accuracy Analysismentioning
confidence: 99%
“…The extensive comparative analysis shows that the presented technique (WeSed) excels better outcome with respect to both labeled and unlabeled image annotation.  Scope of applicability of [15]: Image Annotation Li et al [16] have proposed an efficient design exploration (DSE) method for semi-supervised ensemble learning (SSEL) using Latin cube sampling technique. The method is evaluated based on SSEL by considering some benchmarks and hence the present method shows enhanced performance by reducing time, cost and accuracy enhancement.…”
Section: Related Workmentioning
confidence: 99%