Research

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 around a particular model or field. For instance, in image classification, techniques have been created to deceive models that identify traffic signs by making minor…

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 dimensions m×q, representing labels that we intend to break down into the m × q′ Y′ latent label matrix and the second q′ × q…

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 of data and predictions based on patterns in the data. Research in cheminformatics includes predicting metabolic pathways, predicting toxicity, and analyzing environmental data. It is…

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 of this research area linking together diverse application areas such as environmental sciences, atmospheric science, agriculture, or social science.

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 and data are biased. More targeted efforts to reduce or eliminate training data biases require either manual adjustments of the models, domain knowledge, or assume…

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 as sales, prices, or customer behavior. Time series data can be used to predict future values, identify trends, and understand the relationships between variables. Our…