Kristof Schröder
After completing his PhD in applied mathematics, specializing in applied
harmonic and numerical analysis, Kristof developed a keen interest in the
rapidly evolving field of artificial intelligence. This interest inspired
him to transition his career towards AI engineering,
where he spent the next five years working on various machine learning
projects. In May 2023, he joined the TransferLab team at appliedAI Institute.
Session
Data valuation techniques compute the contribution of training points to the final performance of machine learning models. They are part of so-called data-centric ML, with immediate applications in data engineering like data pruning or improved collection processes, and in model debugging and development. In this talk we demonstrate how the open source library pyDVL can be used to detect mislabeled and out-of-distribution samples with little effort. We cover the core ideas behind the most successful algorithms and illustrate how they can be used to inspect your data to extract the most out of it.