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Tag: machine learning
Machine Learning (ML) deals with how computer programs can learn and improve at performing a specific task when trained on historical data. ML is divided into unsupervised learning (such as clustering and topic modeling) and supervised learning (training a system on annotated examples). ML has been a central part of my research since my PhD studies, and even ended up in my thesis title.
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Human, What Must I Tell You?
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Pipeline Infrastructure Required to Meet the Requirements on AI
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Can RE Help to Better Prepare Industrial AI for the Commercial Scale?
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Enabling Image Recognition on Constrained Devices Using Neural Network Pruning and a CycleGAN
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Requirements Engineering for Machine Learning: Perspectives from Data Scientists
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Performance Analysis of Out-of-Distribution Detection on Various Trained Neural Networks
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SZZ Unleashed: An Open Implementation of the SZZ Algorithm – Featuring Example Usage in a Study of Just-in-Time Bug Prediction for the Jenkins Project
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Machine Learning to Guide Performance Testing: An Autonomous Test Framework
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