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Absolute convergence and error thresholds in non-active adaptive sampling
(Elsevier Inc., 2022-05)
[Abstract] Non-active adaptive sampling is a way of building machine learning models from a training data base which are supposed to dynamically and automatically derive guaranteed sample size. In this context and regardless ...
Surfing the Modeling of pos Taggers in Low-Resource Scenarios
(MDPI, 2022-09-27)
[Abstract] The recent trend toward the application of deep structured techniques has revealed the
limits of huge models in natural language processing. This has reawakened the interest in traditional
machine learning ...