Johannes Fürnkranz
Johannes Kepler Universität Linz
H-index: 51
Europe-Austria
Top articles of Johannes Fürnkranz
Title | Journal | Author(s) | Publication Date |
|---|---|---|---|
Layerwise Learning of Mixed Conjunctive and Disjunctive Rule Sets | Florian Beck Johannes Fürnkranz Van Quoc Phuong Huynh | 2023/9/18 | |
Weighting Information Sets with Siamese Neural Networks in Reconnaissance Blind Chess | Timo Bertram Johannes Fürnkranz Martin Müller | 2023/8/21 | |
On the efficient implementation of classification rule learning | Advances in Data Analysis and Classification | Michael Rapp Johannes Fürnkranz Eyke Hüllermeier | 2023/7/27 |
Tree-based dynamic classifier chains | Machine Learning | Eneldo Loza Mencía Moritz Kulessa Simon Bohlender Johannes Fürnkranz | 2023/11 |
An Empirical comparison of interpretable models to post-hoc explanations | AI | Parisa Mahya Johannes Fürnkranz | 2023/5/19 |
On Sampling Information Sets to Learn from Imperfect Information | Timo Bertram Johannes Fürnkranz Martin Müller | 2023/10/13 | |
Efficient learning of large sets of locally optimal classification rules | Machine Learning | Van Quoc Phuong Huynh Johannes Fürnkranz Florian Beck | 2023/2 |
Probabilistic Scoring Lists for Interpretable Machine Learning | Jonas Hanselle Johannes Fürnkranz Eyke Hüllermeier | 2023/10/8 | |
Incremental Update of Locally Optimal Classification Rules | Van Quoc Phuong Huynh Florian Beck Johannes Fürnkranz | 2022/10/10 | |
Comparing boosting and bagging for decision trees of rankings | Journal of Classification | Antonella Plaia Simona Buscemi Johannes Fürnkranz Eneldo Loza Mencía | 2022/3 |
Unsupervised alignment of distributional word embeddings | Aïssatou Diallo Johannes Fürnkranz | 2022/9/12 | |
GausSetExpander: A Simple Approach for Entity Set Expansion | arXiv preprint arXiv:2202.13649 | Aïssatou Diallo Johannes Fürnkranz | 2022/2/28 |
The Machine Reconnaissance Blind Chess Tournament of NeurIPS 2022 | Ryan W Gardner Gino Perrotta Anvay Shah Shivaram Kalyanakrishnan Kevin A Wang | 2022/8/31 | |
A flexible class of dependence-aware multi-label loss functions | Machine Learning | Eyke Hüllermeier Marcel Wever Eneldo Loza Mencia Johannes Fürnkranz Michael Rapp | 2022/2 |
Supervised and reinforcement learning from observations in reconnaissance blind chess | Timo Bertram Johannes Fürnkranz Martin Müller | 2022/8/21 | |
Correlation-based discovery of disease patterns for syndromic surveillance | Frontiers in big Data | Michael Rapp Moritz Kulessa Eneldo Loza Mencía Johannes Fürnkranz | 2022/1/13 |
Quantity vs Quality: Investigating the Trade-Off between Sample Size and Label Reliability | arXiv preprint arXiv:2204.09462 | Timo Bertram Johannes Fürnkranz Martin Müller | 2022/4/20 |
Towards Deep and Interpretable Rule Learning | Johannes Fürnkranz | 2022 | |
Gradient-based label binning in multi-label classification | Michael Rapp Eneldo Loza Mencía Johannes Fürnkranz Eyke Hüllermeier | 2021 | |
Sum-Product Networks for Early Outbreak Detection of Emerging Diseases | Artificial Intelligence in Medicine: 19th International Conference on Artificial Intelligence in Medicine, AIME 2021, Virtual Event, June 15–18, 2021, Proceedings | Johannes Fürnkranz | 2021/6/8 |
Co-Authors
