| The effect of random seeds for data splitting on recommendation accuracy L Wegmeth, T Vente, L Purucker, J Beel Perspectives on the Evaluation of Recommender Systems Workshop (PERSPECTIVES …, 2023 | 12 | 2023 |
| Accurate predictions on small data with a tabular foundation model N Hollmann, S Müller, L Purucker, A Krishnakumar, M Körfer, SB Hoo, ... Nature 637 (8045), 319-326, 2025 | 9 | 2025 |
| Assembled-OpenML: Creating Efficient Benchmarks for Ensembles in AutoML with OpenML L Purucker, J Beel First Conference on Automated Machine Learning (Late-Breaking Workshop), 2022 | 8 | 2022 |
| CMA-ES for Post Hoc Ensembling in AutoML: A Great Success and Salvageable Failure L Purucker, J Beel International Conference on Automated Machine Learning, 1/1-23, 2023 | 5 | 2023 |
| Don't Waste Your Time: Early Stopping Cross-Validation E Bergman*, L Purucker*, F Hutter AutoML Conference 2024, 2024 | 4 | 2024 |
| HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models RS Sukthanker, A Zela, B Staffler, A Klein, L Purucker, JKH Franke, ... arXiv preprint arXiv:2405.10299, 2024 | 2 | 2024 |
| DAFT: Data-Aware Fine-Tuning of Foundation Models for Efficient and Effective Medical Image Segmentation AT Pfefferle, L Purucker, F Hutter CVPR 2024: Segment Anything In Medical Images On Laptop, 2024 | 2 | 2024 |
| Q(D)O-ES: Population-based Quality (Diversity) Optimisation for Post Hoc Ensemble Selection in AutoML L Purucker, L Schneider, M Anastacio, J Beel, B Bischl, H Hoos International Conference on Automated Machine Learning, 10/1-34, 2023 | 2 | 2023 |
| AMLTK: A Modular AutoML Toolkit in Python E Bergman, M Feurer, A Bahram, AR Balef, L Purucker, S Segel, ... Journal of Open Source Software 9 (100), 6367, 2024 | 1 | 2024 |
| Quick-Tune-Tool: A Practical Tool and its User Guide for Automatically Finetuning Pretrained Models I Rapant, L Purucker, F Ferreira, SP Arango, A Kadra, J Grabocka, ... AutoML Conference 2024 (Workshop Track), 2024 | 1 | 2024 |
| Advancing Biogeographical Ancestry Predictions Through Machine Learning CS Heinzel, L Purucker, F Hutter, P Pfaffelhuber bioRxiv, 2025.01. 31.635898, 2025 | | 2025 |
| Efficient MedSAMs: Segment Anything in Medical Images on Laptop J Ma, F Li, S Kim, R Asakereh, BH Le, DK Nguyen-Vu, A Pfefferle, M Wei, ... arXiv preprint arXiv:2412.16085, 2024 | | 2024 |
| Large Language Models Engineer Too Many Simple Features for Tabular Data J Küken, L Purucker, F Hutter NeurIPS 2024 Third Table Representation Learning Workshop, 2024 | | 2024 |
| Ensembling Finetuned Language Models for Text Classification SP Arango, M Janowski, L Purucker, A Zela, F Hutter, J Grabocka NeurIPS 2024 Workshop on Fine-Tuning in Modern Machine Learning: Principles …, 2024 | | 2024 |
| Transfer Learning for Finetuning Large Language Models T Strangmann, L Purucker, JKH Franke, I Rapant, F Ferreira, F Hutter arXiv preprint arXiv:2411.01195, 2024 | | 2024 |
| Dynamic Post-Hoc Neural Ensemblers SP Arango, M Janowski, L Purucker, A Zela, F Hutter, J Grabocka arXiv preprint arXiv:2410.04520, 2024 | | 2024 |
| Hardware Aware Ensemble Selection for Balancing Predictive Accuracy and Cost J Maier, F Möller, L Purucker AutoML Conference 2024 (Workshop Track), 2024 | | 2024 |
| Revealing the Hidden Impact of Top-N Metrics on Optimization in Recommender Systems L Wegmeth, T Vente, L Purucker ECIR 2024, 2024 | | 2024 |
| Estimating the Pruned Search Space Size of Subgroup Discovery L Purucker, F Stamm, F Lemmerich, J Beel 2022 IEEE International Conference on Data Mining (ICDM), 1155-1160, 2022 | | 2022 |
Frank HutterELLIS Institute Tübingen & Professor, University of Freiburg, GermanyEmail verificata su cs.uni-freiburg.de