We’re happy to share that our team won the Best Poster Award at EvoStar 2025 in Trieste, Italy!
Our paper, “Was Tournament Selection All We Ever Needed? A Critical Reflection on Lexicase Selection”, took a fresh look at how we select individuals in genetic programming. We found that tournament selection, when combined with down-sampling, performs similar to lexicase selection while being more efficiently!
Thanks to Alina Geiger and Martin Briesch who represented us in Trieste and presented the poster.
You can check out the paper here if you’re curious about the details.
Nach vielen Jahren am Lehrstuhl verabschieden wir Heike in den wohlverdienten Ruhestand.
Für unser Team und unsere Studierenden war sie stets mit einem Lächeln, einer helfenden Hand und einem offenen Ohr zur Stelle. Heike hat unseren Lehrstuhl durch ihr unermüdlichen Engagement geprägt und bereichert und war damit weit mehr als nur eine organisatorische Stütze.
Wir sagen von Herzen Danke für all die Jahre und wünschen dir für den neuen Lebensabschnitt Gesundheit, Glück und schöne Abenteuer.
Wir werden dich sehr vermissen!
Congratulations to Clarissa Krämer (MSc.), Susanne Schmitt (MSc.), and Prof. Dr. Franz Rothlauf on receiving the Best Student Paper Award at the Medical Informatics Europe (MIE) Conference in Glasgow, Scotland, from May 19-21, 2025.
Their award-winning paper, "Using Machine Learning for the Fusion of Tumor Records on a Real-World Dataset" focuses on consolidating multiple records describing the same tumor into a single record for each tumor. They used an artificial neural network and compared its performance with that of a deterministic, rule-based approach. They used a tabular, real-world dataset that included colorectal, breast, and prostate cancer.
Key findings were that
- Artificial Neural Networks outperform the deterministic rule-based approach.
- The performance depends on the number of features and the distribution of data.
- The predictive performance increases with a lower number of categories within a variable and a more balanced dataset.
Read the paper here: https://pubmed.ncbi.nlm.nih.gov/40380540/
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