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The objective of adversarial learning is to pinpoint vulnerabilities in machine learning models that traditional testing methods cannot detect. It has proven to be effective in various applications, often centered […]
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Kia Ora! I am Luke Chang and I am passionate about building more reliable machine learning models, an artificial intelligence people can trust. I started my machine learning journey by […]
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The aim of matrix decomposition is to express a provided matrix as the outcome of multiplying two or more factor matrices. In this situation, we possess the Y matrix of […]
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Cheminformatics is a field that combines chemistry and computer science to address challenges in chemistry. Machine learning is a key aspect of cheminformatics, allowing for the processing of large amounts […]
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Computational sustainability is an interdisciplinary field of sustainability research, including applied science about the research in sustainable solutions and their implementation. Machine Learning and Data Mining is at the center […]
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Kia Ora!I am Katharina Dost, a PhD student with the School of Computer Science. My research topic is “Identification and Mitigation of Selection Bias” and I would like to use […]
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Current Machine Learning model evaluation methods, e.g., the use of test sets, will only detect whether a model’s predictions match the data. They cannot exclude the possibility that both predictions […]
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Time series analysis focuses on data is a sequence of data points that are collected over time. The data points can be anything that can be measured over time, such […]
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