Tag: machine learning
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We aim to design and develop new methods to attack machine learning models and use the adversarial attacks to define a measure of reliability. Weak performances of models where data […]
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Most chemicals that are currently produced sooner or later end up in the environment, many of them in rivers and other waters. It is essential to know their fate in […]
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An important aspect in the development of novel chemicals is their environmental fate, that is their ability to degrade when released in the environment. To achieve this, the goal is […]
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Adversarial Machine Learning is a field of Machine Learning that focuses on exploiting model vulnerabilities by making use of obtainable information from the model. Studying a model’s weaknesses to adversarial […]
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For a while now, we have seen the trend that neural networks are vastly popular, and a large portion of the machine learning research is dedicated to achieving minor gains […]
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This project aims to investigate the potential benefits of using our newly developed image compression technique, based on multivariate trees, to enhance image processing machine learning models. The objective is […]
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