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ORCIDStefan Wrobel
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- affiliation: Fraunhofer Institute for Intelligent Analysis and Information Systems, Sankt Augustin, Germany
- affiliation: University of Bonn, Germany
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2020 – today
- 2024
[j38]Assaf Landschaft
, Dario Antweiler, Sina Mackay, Sabine Kugler, Stefan Rüping, Stefan Wrobel, Timm Höres, Héctor Allende-Cid:
Implementation and evaluation of an additional GPT-4-based reviewer in PRISMA-based medical systematic literature reviews. Int. J. Medical Informatics 189: 105531 (2024)- [j37]Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Stefan Wrobel, Asja Fischer:
Wasserstein dropout. Mach. Learn. 113(5): 3161-3204 (2024) - 2023
- [j36]Florian Seiffarth, Tamás Horváth, Stefan Wrobel:
Maximal closed set and half-space separations in finite closure systems. Theor. Comput. Sci. 973: 114105 (2023) - [i17]Maximilian Poretschkin, Anna Schmitz, Maram Akila, Linara Adilova, Daniel Becker, Armin B. Cremers, Dirk Hecker, Sebastian Houben, Michael Mock, Julia Rosenzweig, Joachim Sicking, Elena Schulz, Angelika Voss, Stefan Wrobel:
Guideline for Trustworthy Artificial Intelligence - AI Assessment Catalog. CoRR abs/2307.03681 (2023) - 2022
- [j35]Anna Schmitz, Maram Akila, Dirk Hecker, Maximilian Poretschkin, Stefan Wrobel:
The why and how of trustworthy AI. Autom. 70(9): 793-804 (2022) - [j34]Natalia V. Andrienko, Gennady L. Andrienko, Linara Adilova, Stefan Wrobel, Theresa-Marie Rhyne:
Visual Analytics for Human-Centered Machine Learning. IEEE Computer Graphics and Applications 42(1): 123-133 (2022) - [j33]Till Hendrik Schulz, Tamás Horváth, Pascal Welke, Stefan Wrobel:
A generalized Weisfeiler-Lehman graph kernel. Mach. Learn. 111(7): 2601-2629 (2022) - [c89]Till Hendrik Schulz, Pascal Welke, Stefan Wrobel:
Graph Filtration Kernels. AAAI 2022: 8196-8203 - [c88]Florian Seiffarth, Tamás Horváth, Stefan Wrobel:
A Fast Heuristic for Computing Geodesic Closures in Large Networks. DS 2022: 476-490 - [c87]Florian Seiffarth, Tamás Horváth, Stefan Wrobel:
A Simple Heuristic for the Graph Tukey Depth Problem with Potential Applications to Graph Mining. LWDA 2022: 21-32 - [p5]Dirk Hecker, Angelika Voss, Stefan Wrobel:
Data Ecosystems: A New Dimension of Value Creation Using AI and Machine Learning. Designing Data Spaces 2022: 211-224 - [e4]Boris Otto, Michael ten Hompel, Stefan Wrobel:
Designing Data Spaces: The Ecosystem Approach to Competitive Advantage. Springer 2022, ISBN 978-3-030-93975-5 [contents] - [i16]Joachim Sicking, Maram Akila, Jan David Schneider, Fabian Hüger, Peter Schlicht, Tim Wirtz, Stefan Wrobel:
Tailored Uncertainty Estimation for Deep Learning Systems. CoRR abs/2204.13963 (2022) - [i15]Nathalie Paul, Tim Wirtz, Stefan Wrobel, Alexander Kister:
Multi-Agent Neural Rewriter for Vehicle Routing with Limited Disclosure of Costs. CoRR abs/2206.05990 (2022) - [i14]Florian Seiffarth, Tamás Horváth, Stefan Wrobel:
A Fast Heuristic for Computing Geodesic Cores in Large Networks. CoRR abs/2206.07350 (2022) - [i13]Dorina Weichert, Alexander Kister, Sebastian Houben, Gunar Ernis, Stefan Wrobel:
Robustness in Fatigue Strength Estimation. CoRR abs/2212.01136 (2022) - 2021
- [j32]Gennady L. Andrienko, Natalia V. Andrienko, Gabriel Anzer, Pascal Bauer, Guido Budziak, Georg Fuchs, Dirk Hecker, Hendrik Weber, Stefan Wrobel:
Constructing Spaces and Times for Tactical Analysis in Football. IEEE Trans. Vis. Comput. Graph. 27(4): 2280-2297 (2021) - [j31]Natalia V. Andrienko, Gennady L. Andrienko, Silvia Miksch, Heidrun Schumann, Stefan Wrobel:
A theoretical model for pattern discovery in visual analytics. Vis. Informatics 5(1): 23-42 (2021) - [c86]Eike Stadtländer, Tamás Horváth, Stefan Wrobel:
Learning Weakly Convex Sets in Metric Spaces. ECML/PKDD (2) 2021: 200-216 - [i12]Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Asja Fischer, Stefan Wrobel:
A Novel Regression Loss for Non-Parametric Uncertainty Optimization. CoRR abs/2101.02726 (2021) - [i11]Till Hendrik Schulz, Tamás Horváth, Pascal Welke, Stefan Wrobel:
A Generalized Weisfeiler-Lehman Graph Kernel. CoRR abs/2101.08104 (2021) - [i10]Eike Stadtländer, Tamás Horváth, Stefan Wrobel:
Learning Weakly Convex Sets in Metric Spaces. CoRR abs/2105.06251 (2021) - [i9]Till Hendrik Schulz, Pascal Welke, Stefan Wrobel:
Graph Filtration Kernels. CoRR abs/2110.11862 (2021) - 2020
- [j30]Daniel Trabold, Tamás Horváth, Stefan Wrobel:
Effective approximation of parametrized closure systems over transactional data streams. Mach. Learn. 109(6): 1147-1177 (2020) - [c85]Pascal Welke, Fouad Alkhoury, Christian Bauckhage, Stefan Wrobel:
Decision Snippet Features. ICPR 2020: 4260-4267 - [c84]Pascal Welke, Florian Seiffarth, Michael Kamp, Stefan Wrobel:
HOPS: Probabilistic Subtree Mining for Small and Large Graphs. KDD 2020: 1275-1284 - [c83]Florian Seiffarth, Tamás Horváth, Stefan Wrobel:
Maximum Margin Separations in Finite Closure Systems. ECML/PKDD (1) 2020: 3-18 - [c82]Christian Bauckhage, Rafet Sifa, Stefan Wrobel:
Adiabatic Quantum Computing for Max-Sum Diversification. SDM 2020: 343-351 - [i8]Florian Seiffarth, Tamás Horváth, Stefan Wrobel:
Maximal Closed Set and Half-Space Separations in Finite Closure Systems. CoRR abs/2001.04417 (2020) - [i7]Tiansi Dong, Chengjiang Li, Christian Bauckhage, Juanzi Li, Stefan Wrobel, Armin B. Cremers:
Learning Syllogism with Euler Neural-Networks. CoRR abs/2007.07320 (2020) - [i6]Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Asja Fischer, Stefan Wrobel:
Second-Moment Loss: A Novel Regression Objective for Improved Uncertainties. CoRR abs/2012.12687 (2020)
2010 – 2019
- 2019
- [j29]Pascal Welke, Tamás Horváth, Stefan Wrobel:
Probabilistic and exact frequent subtree mining in graphs beyond forests. Mach. Learn. 108(7): 1137-1164 (2019) - [c81]Rajkumar Ramamurthy, Christian Bauckhage, Rafet Sifa, Jannis Schücker, Stefan Wrobel:
Leveraging Domain Knowledge for Reinforcement Learning Using MMC Architectures. ICANN (2) 2019: 595-607 - [c80]Claudia Loebbecke, Omar El Sawy, Atreyi Kankanhalli, M. Lynne Markus, Dov Te'eni, Stefan Wrobel:
Artificial Intelligence Meets IS Researchers: Can it Replace Us? ICIS 2019 - [c79]Christian Bauckhage, Nico Piatkowski, Rafet Sifa, Dirk Hecker, Stefan Wrobel:
A QUBO Formulation of the k-Medoids Problem. LWDA 2019: 54-63 - [c78]Christian Bauckhage, Rafet Sifa, Dirk Hecker, Stefan Wrobel:
Max-Sum Dispersion via Quantum Annealing. LWDA 2019: 64-68 - [c77]Annika Pick, Tamás Horváth, Stefan Wrobel:
Support Estimation in Frequent Itemset Mining by Locality Sensitive Hashing. LWDA 2019: 156-160 - [c76]Florian Seiffarth, Tamás Horváth, Stefan Wrobel:
Maximal Closed Set and Half-Space Separations in Finite Closure Systems. ECML/PKDD (1) 2019: 21-37 - 2018
- [j28]Pascal Welke, Tamás Horváth, Stefan Wrobel:
Probabilistic frequent subtrees for efficient graph classification and retrieval. Mach. Learn. 107(11): 1847-1873 (2018) - [c75]Rajkumar Ramamurthy, Christian Bauckhage, Rafet Sifa, Stefan Wrobel:
Policy Learning Using SPSA. ICANN (3) 2018: 3-12 - [c74]Christian Bauckhage, César Ojeda, Rafet Sifa, Stefan Wrobel:
Adiabatic Quantum Computing for Kernel k=2 Means Clustering. LWDA 2018: 21-32 - [c73]Christian Bauckhage, César Ojeda, Jannis Schücker, Rafet Sifa, Stefan Wrobel:
Informed Machine Learning Through Functional Composition. LWDA 2018: 33-37 - [c72]Michael Kamp, Linara Adilova, Joachim Sicking, Fabian Hüger, Peter Schlicht, Tim Wirtz, Stefan Wrobel:
Efficient Decentralized Deep Learning by Dynamic Model Averaging. ECML/PKDD (1) 2018: 393-409 - [c71]Till Hendrik Schulz, Tamás Horváth, Pascal Welke, Stefan Wrobel:
Mining Tree Patterns with Partially Injective Homomorphisms. ECML/PKDD (2) 2018: 585-601 - [i5]Michael Kamp, Linara Adilova, Joachim Sicking, Fabian Hüger, Peter Schlicht, Tim Wirtz, Stefan Wrobel:
Efficient Decentralized Deep Learning by Dynamic Model Averaging. CoRR abs/1807.03210 (2018) - 2017
- [c70]Christian Bauckhage, Eduardo Brito, Kostadin Cvejoski, César Ojeda, Rafet Sifa, Stefan Wrobel:
Ising Models for Binary Clustering via Adiabatic Quantum Computing. EMMCVPR 2017: 3-17 - [c69]Rajkumar Ramamurthy, Christian Bauckhage, Krisztián Búza, Stefan Wrobel:
Using Echo State Networks for Cryptography. ICANN (2) 2017: 663-671 - [c68]Katrin Ullrich, Michael Kamp, Thomas Gärtner, Martin Vogt, Stefan Wrobel:
Co-Regularised Support Vector Regression. ECML/PKDD (2) 2017: 338-354 - [r4]Thomas Gärtner, Tamás Horváth, Stefan Wrobel:
Graph Kernels. Encyclopedia of Machine Learning and Data Mining 2017: 579-581 - [r3]Tamás Horváth, Stefan Wrobel:
Learning from Structured Data. Encyclopedia of Machine Learning and Data Mining 2017: 712-715 - [i4]Rajkumar Ramamurthy, Christian Bauckhage, Krisztián Búza, Stefan Wrobel:
Using Echo State Networks for Cryptography. CoRR abs/1704.01046 (2017) - 2016
- [c67]Pascal Welke, Tamás Horváth, Stefan Wrobel:
Min-Hashing for Probabilistic Frequent Subtree Feature Spaces. DS 2016: 67-82 - [c66]Katrin Ullrich, Michael Kamp, Thomas Gärtner, Martin Vogt, Stefan Wrobel:
Ligand-Based Virtual Screening with Co-regularised Support Vector Regression. ICDM Workshops 2016: 261-268 - 2015
- [j27]Stefan Wrobel, Hans Voss, Joachim Köhler, Uwe Beyer, Sören Auer:
Big Data, Big Opportunities - Anwendungssituation und Forschungsbedarf des Themas Big Data in Deutschland. Inform. Spektrum 38(5): 370-378 (2015) - [c65]Daniel Maier, Stefan Wrobel, Maren Bennewitz:
Whole-body self-calibration via graph-optimization and automatic configuration selection. ICRA 2015: 5662-5668 - [c64]Pascal Welke, Tamás Horváth, Stefan Wrobel:
Probabilistic Frequent Subtree Kernels. NFMCP 2015: 179-193 - 2014
- [c63]Stefan Wrobel:
Big Data Analytics - Vom Maschinellen Lernen zur DataScience. GI-Jahrestagung 2014: 53 - [c62]Pascal Welke, Tamás Horváth, Stefan Wrobel:
On the Complexity of Frequent Subtree Mining in Very Simple Structures. ILP 2014: 194-209 - 2013
- [b2]Gennady L. Andrienko, Natalia V. Andrienko, Peter Bak, Daniel A. Keim, Stefan Wrobel:
Visual Analytics of Movement. Springer 2013, ISBN 978-3-642-37582-8, pp. I-XVIII, 1-387 - [j26]Gennady L. Andrienko, Natalia V. Andrienko, Christophe Hurter, Salvatore Rinzivillo, Stefan Wrobel:
Scalable Analysis of Movement Data for Extracting and Exploring Significant Places. IEEE Trans. Vis. Comput. Graph. 19(7): 1078-1094 (2013) - [c61]Mario Boley, Michael Mampaey, Bo Kang, Pavel Tokmakov, Stefan Wrobel:
One click mining: interactive local pattern discovery through implicit preference and performance learning. IDEA@KDD 2013: 27-35 - [p4]Stefan Wrobel, Thorsten Joachims, Katharina Morik:
Maschinelles Lernen und Data Mining. Handbuch der Künstlichen Intelligenz 2013: 405-472 - 2012
- [j25]Christine Körner, Michael May, Stefan Wrobel:
Special Issue on Spatiotemporal Modeling and Analysis. Künstliche Intell. 26(3): 213-214 (2012) - [j24]Christine Körner, Michael May, Stefan Wrobel:
Spatiotemporal Modeling and Analysis - Introduction and Overview. Künstliche Intell. 26(3): 215-221 (2012) - [c60]Thomas Liebig, Zhao Xu, Michael May, Stefan Wrobel:
Pedestrian Quantity Estimation with Trajectory Patterns. ECML/PKDD (2) 2012: 629-643 - [i3]Daniel A. Keim, Fabrice Rossi, Thomas Seidl, Michel Verleysen, Stefan Wrobel:
Information Visualization, Visual Data Mining and Machine Learning (Dagstuhl Seminar 12081). Dagstuhl Reports 2(2): 58-83 (2012) - 2011
- [j23]S. V. N. Vishwanathan, Samuel Kaski, Jennifer Neville, Stefan Wrobel:
Introduction to the special issue on mining and learning with graphs. Mach. Learn. 82(2): 91-93 (2011) - [j22]Gennady L. Andrienko, Natalia V. Andrienko, Peter Bak, Daniel A. Keim, Slava Kisilevich, Stefan Wrobel:
A conceptual framework and taxonomy of techniques for analyzing movement. J. Vis. Lang. Comput. 22(3): 213-232 (2011) - [j21]Gennady L. Andrienko, Natalia V. Andrienko, Daniel A. Keim, Alan M. MacEachren, Stefan Wrobel:
Challenging problems of geospatial visual analytics. J. Vis. Lang. Comput. 22(4): 251-256 (2011) - [c59]Gennady L. Andrienko, Natalia V. Andrienko, Christophe Hurter, Salvatore Rinzivillo, Stefan Wrobel:
From movement tracks through events to places: Extracting and characterizing significant places from mobility data. IEEE VAST 2011: 161-170 - 2010
- [j20]Tamás Horváth, Jan Ramon, Stefan Wrobel:
Frequent subgraph mining in outerplanar graphs. Data Min. Knowl. Discov. 21(3): 472-508 (2010) - [j19]Mario Boley, Tamás Horváth, Axel Poigné, Stefan Wrobel:
Listing closed sets of strongly accessible set systems with applications to data mining. Theor. Comput. Sci. 411(3): 691-700 (2010) - [j18]Anna Monreale, Gennady L. Andrienko, Natalia V. Andrienko, Fosca Giannotti, Dino Pedreschi, Salvatore Rinzivillo, Stefan Wrobel:
Movement Data Anonymity through Generalization. Trans. Data Priv. 3(2): 91-121 (2010) - [c58]Christine Körner, Dirk Hecker, Michael May, Stefan Wrobel:
Visit Potential: A Common Vocabulary for the Analysis of Entity-Location Interactions in Mobility Applications. AGILE Conf. 2010: 79-95 - [c57]Sven Becker, Marion Borowski, Melanie Gnasa, Kai Stalmann, Stefan Wrobel:
eHumanities: Intelligent Analysis and Information System for Humanities and Culture. GI Jahrestagung (2) 2010: 552-556 - [c56]Sebastian Bothe, Thomas Gärtner, Stefan Wrobel:
On-Line Handwriting Recognition with Parallelized Machine Learning Algorithms. KI 2010: 82-90 - [c55]Mario Boley, Tamás Horváth, Axel Poigné, Stefan Wrobel:
Listing closed sets of strongly accessible set systems with applications to data. LWA 2010: 33 - [p3]Christine Körner, Dirk Hecker, Maike Krause-Traudes, Michael May, Simon Scheider, Daniel Schulz, Hendrik Stange, Stefan Wrobel:
Spatial Data Mining in Practice: Principles and Case Studies. Data Mining for Business Applications 2010: 164-178 - [e3]Daniel A. Keim, Stefan Wrobel:
Scalable Visual Analytics, 21.11. - 26.11.2010. Dagstuhl Seminar Proceedings 10471, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Germany 2010 [contents] - [r2]Thomas Gärtner, Tamás Horváth, Stefan Wrobel:
Graph Kernels. Encyclopedia of Machine Learning 2010: 467-469 - [r1]Tamás Horváth, Stefan Wrobel:
Learning from Structured Data. Encyclopedia of Machine Learning 2010: 580-584 - [i2]Daniel A. Keim, Stefan Wrobel:
10471 Abstracts Collection - Scalable Visual Analytics. Scalable Visual Analytics 2010 - [i1]Daniel A. Keim, Stefan Wrobel:
10471 Executive Summary - Scalable Visual Analytics. Scalable Visual Analytics 2010
2000 – 2009
- 2009
- [j17]Mario Boley, Tamás Horváth, Stefan Wrobel:
Efficient discovery of interesting patterns based on strong closedness. Stat. Anal. Data Min. 2(5-6): 346-360 (2009) - [c54]Shivani Seth, Stefan Rüping, Stefan Wrobel:
Metadata Extraction using Text Mining. HealthGrid 2009: 95-104 - [c53]Dennis Wegener, Michael Mock, Deyaa Adranale, Stefan Wrobel:
Toolkit-Based High-Performance Data Mining of Large Data on MapReduce Clusters. ICDM Workshops 2009: 296-301 - [c52]Tamás Horváth, Gerhard Paass, Frank Reichartz, Stefan Wrobel:
A Logic-Based Approach to Relation Extraction from Texts. ILP 2009: 34-48 - [c51]Hongqi Wang, Olana Missura, Thomas Gärtner, Stefan Wrobel:
Context-Based Clustering of Image Search Results. KI 2009: 153-160 - [c50]Mario Boley, Tamás Horváth, Stefan Wrobel:
Efficient Discovery of Interesting Patterns Based on Strong Closedness. SDM 2009: 1002-1013 - 2008
- [j16]Hanna Geppert, Tamás Horváth, Thomas Gärtner, Stefan Wrobel, Jürgen Bajorath:
Support-Vector-Machine-Based Ranking Significantly Improves the Effectiveness of Similarity Searching Using 2D Fingerprints and Multiple Reference Compounds. J. Chem. Inf. Model. 48(4): 742-746 (2008) - [c49]Natalja Punko, Stefan Rüping, Stefan Wrobel:
Facilitating Clinico-Genomic Knowledge Discovery by Automatic Selection of KDD Processes. LWA 2008: 84-86 - [c48]Henrik Grosskreutz, Stefan Rüping, Stefan Wrobel:
Tight Optimistic Estimates for Fast Subgroup Discovery. ECML/PKDD (1) 2008: 440-456 - [p2]Gennady L. Andrienko, Natalia V. Andrienko, Ioannis Kopanakis, Arend Ligtenberg, Stefan Wrobel:
Visual Analytics Methods for Movement Data. Mobility, Data Mining and Privacy 2008: 375-410 - 2007
- [j15]Gennady L. Andrienko, Natalia V. Andrienko, Piotr Jankowski, Daniel A. Keim, Menno-Jan Kraak, Alan M. MacEachren, Stefan Wrobel:
Geovisual analytics for spatial decision support: Setting the research agenda. Int. J. Geogr. Inf. Sci. 21(8): 839-857 (2007) - [j14]Gennady L. Andrienko, Natalia V. Andrienko, Stefan Wrobel:
Visual analytics tools for analysis of movement data. SIGKDD Explor. 9(2): 38-46 (2007) - [c47]Mario Boley, Tamás Horváth, Axel Poigné, Stefan Wrobel:
Efficient Closed Pattern Mining in Strongly Accessible Set Systems. MLG 2007 - [c46]Shankar Vembu, Thomas Gärtner, Stefan Wrobel:
Semidefinite Ranking on Graphs. MLG 2007 - [c45]Mario Boley, Tamás Horváth, Axel Poigné, Stefan Wrobel:
Efficient Closed Pattern Mining in Strongly Accessible Set Systems (Extended Abstract). PKDD 2007: 382-389 - 2006
- [j13]Stefan Wrobel:
Intelligenz ist Lernen - 50 Jahre Künstliche Intelligenz und Maschinelles Lernen. Künstliche Intell. 20(4): 40-42 (2006) - [c44]Christine Körner, Stefan Wrobel:
Multi-class Ensemble-Based Active Learning. ECML 2006: 687-694 - [c43]Ulf Brefeld, Thomas Gärtner, Tobias Scheffer, Stefan Wrobel:
Efficient co-regularised least squares regression. ICML 2006: 137-144 - [c42]Tamás Horváth, Jan Ramon, Stefan Wrobel:
Frequent subgraph mining in outerplanar graphs. KDD 2006: 197-206 - [c41]Tamás Horváth, Jan Ramon, Stefan Wrobel:
Frequent Subgraph Mining in Outerplanar Graphs. LWA 2006: 290-296 - [c40]Christine Körner, Stefan Wrobel:
Bias-Free Hypothesis Evaluation in Multirelational Domains. PAKDD 2006: 668-672 - [c39]Tamás Horváth, Susanne Hoche, Stefan Wrobel:
Effective rule induction from labeled graphs. SAC 2006: 611-616 - [c38]Christine Körner, Stefan Wrobel:
Bias-free hypothesis evaluation in multirelational domains. SAC 2006: 639-640 - 2005
- [c37]Stefan Wrobel, Thomas Gärtner, Tamás Horváth:
Kernels for Predictive Graph Mining. GfKl 2005: 75-86 - [c36]Christine Körner, Stefan Wrobel:
Bias-free Hypothesis Evaluation in Multirelational Domains. LWA 2005: 172-177 - [e2]Luc De Raedt, Stefan Wrobel:
Machine Learning, Proceedings of the Twenty-Second International Conference (ICML 2005), Bonn, Germany, August 7-11, 2005. ACM International Conference Proceeding Series 119, ACM 2005, ISBN 1-59593-180-5 [contents] - 2004
- [c35]Lourdes Peña Castillo, Stefan Wrobel:
A comparative study on methods for reducing myopia of hill-climbing search in multirelational learning. ICML 2004 - [c34]Tamás Horváth, Thomas Gärtner, Stefan Wrobel:
Cyclic pattern kernels for predictive graph mining. KDD 2004: 158-167 - 2003
- [j12]Saso Dzeroski, Luc De Raedt, Stefan Wrobel:
Multirelational data mining 2003: workshop report. SIGKDD Explor. 5(2): 200-202 (2003) - [c33]Thomas Gärtner, Peter A. Flach, Stefan Wrobel:
On Graph Kernels: Hardness Results and Efficient Alternatives. COLT 2003: 129-143 - [c32]Lourdes Peña Castillo, Stefan Wrobel:
Learning Minesweeper with Multirelational Learning. IJCAI 2003: 533-540 - [c31]Susanne Hoche, Stefan Wrobel:
A Comparative Evaluation of Feature Set Evolution Strategies for Multirelational Boosting. ILP 2003: 180-196 - [c30]Mark-A. Krogel, Simon Alan Rawles, Filip Zelezný, Peter A. Flach, Nada Lavrac, Stefan Wrobel:
Comparative Evaluation of Approaches to Propositionalization. ILP 2003: 197-214 - [p1]Stefan Wrobel, Katharina Morik, Thorsten Joachims:
Maschinelles Lernen und Data Mining. Handbuch der Künstlichen Intelligenz 2003: 517-597 - 2002
- [j11]Tobias Scheffer, Stefan Wrobel:
Finding the Most Interesting Patterns in a Database Quickly by Using Sequential Sampling. J. Mach. Learn. Res. 3: 833-862 (2002) - [j10]Tobias Scheffer, Stefan Wrobel, Borislav Popov, Damyan Ognianov, Christian Decomain, Susanne Hoche:
Lerning Hidden Markov Models for Information Extraction Actively from Partially Labeled Text. Künstliche Intell. 16(2): 17-22 (2002) - [c29]Mark-A. Krogel, Stefan Wrobel:
Feature Selection for Propositionalization. Discovery Science 2002: 430-434 - [c28]Susanne Hoche, Stefan Wrobel:
Scaling Boosting by Margin-Based Inclusionof Features and Relations. ECML 2002: 148-160 - [c27]Lourdes Peña Castillo, Stefan Wrobel:
Macro-Operators in Multirelational Learning: A Search-Space Reduction Technique. ECML 2002: 357-368 - [c26]Lourdes Peña Castillo, Stefan Wrobel:
On the Stability of Example-Driven Learning Systems: A Case Study in Multirelational Learning. MICAI 2002: 321-330 - [c25]Tobias Scheffer, Stefan Wrobel:
A Scalable Constant-Memory Sampling Algorithm for Pattern Discovery in Large Databases. PKDD 2002: 397-409 - 2001
- [j9]Tamás Horváth, Stefan Wrobel, Uta Bohnebeck:
Relational Instance-Based Learning with Lists and Terms. Mach. Learn. 43(1/2): 53-80 (2001) - [c24]Tamás Horváth, Stefan Wrobel:
Towards Discovery of Deep and Wide First-Order Structures: A Case Study in the Domain of Mutagenicity. Discovery Science 2001: 100-112 - [c23]Stefan Wrobel:
Scalability, Search, and Sampling: From Smart Algorithms to Active Discovery. ECML 2001: 615 - [c22]Tobias Scheffer, Christian Decomain, Stefan Wrobel:
Mining the Web with Active Hidden Markov Models. ICDM 2001: 645-646 - [c21]Tobias Scheffer, Stefan Wrobel:
Incremental Maximization of Non-Instance-Averaging Utility Functions with Applications to Knowledge Discovery Problems. ICML 2001: 481-488 - [c20]Tobias Scheffer, Christian Decomain, Stefan Wrobel:
Active Hidden Markov Models for Information Extraction. IDA 2001: 309-318 - [c19]Susanne Hoche, Stefan Wrobel:
Relational Learning Using Constrained Confidence-Rated Boosting. ILP 2001: 51-64 - [c18]Mark-A. Krogel, Stefan Wrobel:
Transformation-Based Learning Using Multirelational Aggregation. ILP 2001: 142-155 - [c17]Stefan Wrobel:
Scalability, Search, and Sampling: From Smart Algorithms to Active Discovery. PKDD 2001: 507 - 2000
- [c16]Mathias Kirsten, Stefan Wrobel:
Extending K-Means Clustering to First-Order Representations. ILP 2000: 112-129 - [c15]Tobias Scheffer, Stefan Wrobel:
A sequential sampling algorithm for a general class of utility criteria. KDD 2000: 330-334
1990 – 1999
- 1999
- [c14]Tamás Horváth, Zoltán Alexin, Tibor Gyimóthy, Stefan Wrobel:
Application of Different Learning Methods to Hungarian Part-of-Speech Tagging. ILP 1999: 128-139 - 1998
- [j8]Stefan Wrobel:
Data Mining und Wissensentdeckung in Datenbanken. Künstliche Intell. 12(1): 6-10 (1998) - [j7]Stefan Wrobel:
Data Mining Serviceteil. Künstliche Intell. 12(1): 58-59 (1998) - [j6]Mathias Kirsten, Stefan Wrobel, F. Wilhelm Dahmen, Hans-Christoph Dahmen:
Einsatz von Data Mining-Techniken zur Analyse ökologischer Standort- und Pflanzendaten. Künstliche Intell. 12(2): 39-42 (1998) - [c13]Stefan Wrobel:
Scalability Issues in Inductive Logic Programming. ALT 1998: 11-30 - [c12]Uta Bohnebeck, Werner Sälter, Tamás Horváth, Stefan Wrobel, Dietmar Blohm:
Measuring similarity of RNA structures by relational instance-based learning: A first step toward detecting RNA signal structures in silico. German Conference on Bioinformatics 1998 - [c11]Uta Bohnebeck, Tamás Horváth, Stefan Wrobel:
Term Comparisons in First-Order Similarity Measures. ILP 1998: 65-79 - [c10]Mathias Kirsten, Stefan Wrobel:
Relational Distance-Based Clustering. ILP 1998: 261-270 - 1997
- [j5]Stefan Wrobel:
Data Mining - Das aktuelle Schlagwort. Künstliche Intell. 11(1): 22 (1997) - [c9]Stefan Wrobel:
An Algorithm for Multi-relational Discovery of Subgroups. PKDD 1997: 78-87 - [c8]Werner Emde, Jörg Rahmer, Angi Voß, Christian Beilken, Josef Börding, Wolfgang Orth, Ulrike Petersen, Jörg Walter Schaaf, Michael Spenke, Stefan Wrobel:
Interactive Configuration in KIKon. XPS 1997: 79-91 - 1996
- [j4]Nada Lavrac, Stefan Wrobel:
Induktive Logikprogrammierung - Grundlagen und Techniken. Künstliche Intell. 10(3): 46-54 (1996) - [c7]Stefan Wrobel, Dietrich Wettschereck, Edgar Sommer, Werner Emde:
Extensibility in Data Mining Systems. KDD 1996: 214-219 - 1995
- [e1]Nada Lavrac, Stefan Wrobel:
Machine Learning: ECML-95, 8th European Conference on Machine Learning, Heraclion, Crete, Greece, April 25-27, 1995, Proceedings. Lecture Notes in Computer Science 912, Springer 1995, ISBN 3-540-59286-5 [contents] - 1994
- [b1]Stefan Wrobel:
Concept formation and knowledge revision: a demand driven approach to representation change. Technical University of Dortmund, Germany, Kluwer 1994, ISBN 978-0-7923-9500-3, pp. I-XIV, 1-240 - [j3]Stefan Wrobel:
Concept Formation During Interactive Theory Revision. Mach. Learn. 14(1): 169-191 (1994) - 1993
- [c6]Stefan Wrobel:
On the Proper Definition of Minimality in Specialization and Theory Revision. ECML 1993: 65-82 - 1991
- [j2]Stefan Wrobel:
Die Umweltverankerung von Begriffsbildungsprozessen. Künstliche Intell. 5(1): 22-26 (1991) - [c5]Francesco Bergadano, Floriana Esposito, Céline Rouveirol, Stefan Wrobel:
Panel: Evaluating and Changing Representation in Concept Acquisition. EWSL 1991: 89-100 - [c4]Stefan Wrobel:
Towards a Model of Grounded Concept Formation. IJCAI 1991: 712-719
1980 – 1989
- 1988
- [j1]Stefan Wrobel:
Design Goals for Sloppy Modeling Systems. Int. J. Man Mach. Stud. 29(4): 461-477 (1988) - [c3]Stefan Wrobel:
Automatic Representation Adjustment in an Observational Discovery System. EWSL 1988: 253-262 - 1987
- [c2]Stefan Wrobel:
Higher-order Concepts in a Tractable Knowledge Representation. GWAI 1987: 129-138 - [c1]Stefan Wrobel:
Demand-Driven Concept Formation. Knowledge Representation and Organization in Machine Learning 1987: 289-319
Coauthor Index
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