Active learning (machine learning)
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Even though active learning forms an important pillar of machine learning, deep learning tools are not prevalent within it. Deep… Expand Multi-Task Learning (MTL) is a learning paradigm in machine learning and its aim is to leverage useful information contained in… Expand Automatic Speech Recognition (ASR) has historically been a driving force behind many machine learning (ML) techniques, including… Expand The key idea behind active learning is that a machine learning algorithm can perform better with less training if it is allowed… Expand Active learning is generally defined as any instructional method that engages students in the learning process. In short, active… Expand Dataset shift is a common problem in predictive modeling that occurs when the joint distribution of inputs and outputs differs… Expand Sentiment analysis, also called opinion mining, is a form of information extraction from text of growing research and commercial… Expand This paper is concerned with the class imbalance problem which has been known to hinder the learning performance of… Expand Active learning differs from “learning from examples” in that the learning algorithm assumes at least some control over what part… Expand Support vector machines have met with significant success in numerous real-world learning tasks. However, like most machine… Expand