Kramer, Stefan

37 publications

MLJ 2026 Science-Gym: A Simple Testbed for AI-Driven Scientific Discovery Mattia Cerrato, Lennart Baur, Jannis Brugger, Sajjad Shumaly, Nicholas Schmitt, Edward Finkelstein, Selina Jukic, Lars Münzel, Felix Peter Paul, Pascal Pfannes, Benedikt Rohr, Julius Schellenberg, Philipp Wolf, Stefan Kramer

MLJ 2025 Adaptive Differentiable Trees for Transparent Learning on Data Streams Kirsten Köbschall, Lisa Hartung, Stefan Kramer

MLJ 2025 Neural RELAGGS Lukas Pensel, Stefan Kramer

MLJ 2025 Pairwise Learning to Rank by Neural Networks Revisited: Reconstruction, Theoretical Analysis and Practical Performance Marius Köppel, Alexander Segner, Martin Wagener, Lukas Pensel, Andreas Karwath, Stefan Kramer

AAAI 2024 Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations Cedric Derstroff, Mattia Cerrato, Jannis Brugger, Jan Peters, Stefan Kramer

AAAI 2023 Invariant Representations with Stochastically Quantized Neural Networks Mattia Cerrato, Marius Köppel, Roberto Esposito, Stefan Kramer

ECML-PKDD 2021 Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part I Nuria Oliver, Fernando Pérez-Cruz, Stefan Kramer, Jesse Read, José Antonio Lozano

ECML-PKDD 2021 Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part II Nuria Oliver, Fernando Pérez-Cruz, Stefan Kramer, Jesse Read, José Antonio Lozano

ECML-PKDD 2021 Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part III Nuria Oliver, Fernando Pérez-Cruz, Stefan Kramer, Jesse Read, José Antonio Lozano

IJCAI 2020 A Brief History of Learning Symbolic Higher-Level Representations from Data (And a Curious Look Forward) Stefan Kramer

JMLR 2019 Decoupling Sparsity and Smoothness in the Dirichlet Variational Autoencoder Topic Model Sophie Burkhardt, Stefan Kramer

ECML-PKDD 2019 Pairwise Learning to Rank by Neural Networks Revisited: Reconstruction, Theoretical Analysis and Practical Performance Marius Köppel, Alexander Segner, Martin Wagener, Lukas Pensel, Andreas Karwath, Stefan Kramer

MLJ 2018 Online Multi-Label Dependency Topic Models for Text Classification Sophie Burkhardt, Stefan Kramer

ECML-PKDD 2017 Online Sparse Collapsed Hybrid Variational-Gibbs Algorithm for Hierarchical Dirichlet Process Topic Models Sophie Burkhardt, Stefan Kramer

ECML-PKDD 2016 Online Density Estimation of Heterogeneous Data Streams in Higher Dimensions Michael Geilke, Andreas Karwath, Stefan Kramer

ECML-PKDD 2015 Scavenger - A Framework for Efficient Evaluation of Dynamic and Modular Algorithms Andrey Tyukin, Stefan Kramer, Jörg Wicker

ECML-PKDD 2014 BMaD - A Boolean Matrix Decomposition Framework Andrey Tyukin, Stefan Kramer, Jörg Wicker

MLJ 2011 Efficient Mining for Structurally Diverse Subgraph Patterns in Large Molecular Databases Andreas Maunz, Christoph Helma, Stefan Kramer

ECML-PKDD 2011 Parallel Structural Graph Clustering Madeleine Seeland, Simon A. Berger, Alexandros Stamatakis, Stefan Kramer

AAAI 2010 Fast Conditional Density Estimation for Quantitative Structure-Activity Relationships Fabian Buchwald, Tobias Girschick, Eibe Frank, Stefan Kramer

ECML-PKDD 2010 Latent Structure Pattern Mining Andreas Maunz, Christoph Helma, Tobias Cramer, Stefan Kramer

ECML-PKDD 2010 Online Structural Graph Clustering Using Frequent Subgraph Mining Madeleine Seeland, Tobias Girschick, Fabian Buchwald, Stefan Kramer

MLJ 2008 Inductive Logic Programming for Gene Regulation Prediction Sebastian Fröhler, Stefan Kramer

ECML-PKDD 2008 Kernel-Based Inductive Transfer Ulrich Rückert, Stefan Kramer

MLJ 2008 Margin-Based First-Order Rule Learning Ulrich Rückert, Stefan Kramer

ECML-PKDD 2008 SINDBAD and SiQL: An Inductive Database and Query Language in the Relational Model Jörg Wicker, Lothar Richter, Kristina Kessler, Stefan Kramer

ICML 2006 A Statistical Approach to Rule Learning Ulrich Rückert, Stefan Kramer

MLJ 2006 Introduction to the Special Issue on Multi-Relational Data Mining and Statistical Relational Learning Hendrik Blockeel, David D. Jensen, Stefan Kramer

ICML 2004 Ensembles of Nested Dichotomies for Multi-Class Problems Eibe Frank, Stefan Kramer

ICML 2004 Towards Tight Bounds for Rule Learning Ulrich Rückert, Stefan Kramer

ICML 2003 Stochastic Local Search in K-Term DNF Learning Ulrich Rückert, Stefan Kramer

ECML-PKDD 2002 Phase Transitions and Stochastic Local Search in K-Term DNF Learning Ulrich Rückert, Stefan Kramer, Luc De Raedt

ICML 2002 Transformation-Based Regression Björn Bringmann, Stefan Kramer, Friedrich Neubarth, Hannes Pirker, Gerhard Widmer

ICML 2001 Feature Construction with Version Spaces for Biochemical Applications Stefan Kramer, Luc De Raedt

IJCAI 2001 The Levelwise Version Space Algorithm and Its Application to Molecular Fragment Finding Luc De Raedt, Stefan Kramer

IJCAI 1997 Can We Benefit from Metrics in KBS Development? Stefan Kramer, Hermann Kaindl, Stefan Schlee

AAAI 1996 Structural Regression Trees Stefan Kramer