• Adversarial Learning

    Adversarial Learning

    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 […]

  • Boolean Matrix Decomposition

    Boolean Matrix Decomposition

    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 […]

  • Cheminformatics


    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 […]

  • Computational Sustainability

    Computational Sustainability

    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 […]

  • Reliable Machine Learning

    Reliable Machine Learning

    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 […]

  • Time Series Analysis

    Time Series Analysis

    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 […]