Stefan Kramer

ORCID

Publication Activity (10 Years)

Years Active: 1995-2024
Publications (10 Years): 68

Top Venues

Publications

Cedric Derstroff, Jannis Brugger, Jannis Blüml, Mira Mezini, Stefan Kramer, Kristian Kersting
Amplifying Exploration in Monte-Carlo Tree Search by Focusing on the Unknown. CoRR (2024)
Cedric Derstroff, Mattia Cerrato, Jannis Brugger, Jan Peters, Stefan Kramer
Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations. AAAI (2024)
Mattia Cerrato, Marius Köppel, Philipp Wolf, Stefan Kramer
10 Years of Fair Representations: Challenges and Opportunities. CoRR (2024)
Cedric Derstroff, Mattia Cerrato, Jannis Brugger, Jan Peters, Stefan Kramer
Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations. CoRR (2023)
Stefan Kramer, Mattia Cerrato, Saso Dzeroski, Ross D. King
Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems. CoRR (2023)
Julian Vexler, Stefan Kramer
Identifying Aircraft Motions and Patterns from Magnetometry Data Using a Knowledge-Based Multi-Fusion Approach. FUSION (2023)
Mattia Cerrato, Marius Köppel, Roberto Esposito, Stefan Kramer
Invariant Representations with Stochastically Quantized Neural Networks. AAAI (2023)
Julian Vexler, Stefan Kramer
Classifying Aircraft Categories from Magnetometry Data Using a Hypotheses-Based Multi-Task Framework. ECAI (2023)
Lukas-Malte Bammert, Stefan Kramer, Mattia Cerrato, Ernst Althaus
Privacy-Preserving Learning of Random Forests Without Revealing the Trees. DS (2023)
Mattia Cerrato, Marius Köppel, Alexander Segner, Stefan Kramer
Fair Group-Shared Representations with Normalizing Flows. CoRR (2022)
Mattia Cerrato, Alesia Vallenas Coronel, Marius Köppel, Alexander Segner, Roberto Esposito, Stefan Kramer
Fair Interpretable Representation Learning with Correction Vectors. CoRR (2022)
Mattia Cerrato, Marius Köppel, Roberto Esposito, Stefan Kramer
Invariant Representations with Stochastically Quantized Neural Networks. CoRR (2022)
Lukas Pensel, Stefan Kramer
Neural RELAGGS. CoRR (2022)
Mattia Cerrato, Marius Köppel, Alexander Segner, Stefan Kramer
Fair Interpretable Learning via Correction Vectors. CoRR (2022)
Julia Siekiera, Marius Köppel, Edwin Simpson, Kevin Stowe, Iryna Gurevych, Stefan Kramer
Ranking Creative Language Characteristics in Small Data Scenarios. ICCC (2022)
Weichen Li, Patrick Abels, Zahra Ahmadi, Sophie Burkhardt, Benjamin Schiller, Iryna Gurevych, Stefan Kramer
Topic-Guided Knowledge Graph Construction for Argument Mining. ICBK (2021)
Atif Raza, Stefan Kramer
Pattern Sampling for Shapelet-based Time Series Classification. CoRR (2021)
Ernst Althaus, Mohammad Sadeq Dousti, Stefan Kramer
Fast Private Parameter Learning and Evaluation for Sum-Product Networks. CoRR (2021)
Sophie Burkhardt, Jannis Brugger, Nicolas Wagner, Zahra Ahmadi, Kristian Kersting, Stefan Kramer
Rule Extraction From Binary Neural Networks With Convolutional Rules for Model Validation. Frontiers Artif. Intell. 4 (2021)
Stefan Kramer
Myths and Misconceptions about Machine Learning and How They Are Related to Software Engineering. ENASE (2021)
Stefan Kramer
Myths and Misconceptions about Machine Learning and How They Are Related to Software Engineering. ICEIS (1) (2021)
Patrick Abels, Zahra Ahmadi, Sophie Burkhardt, Benjamin Schiller, Iryna Gurevych, Stefan Kramer
Focusing Knowledge-based Graph Argument Mining via Topic Modeling. CoRR (2021)
Antoine Garcon, Julian Vexler, Dmitry Budker, Stefan Kramer
Deep Neural Networks to Recover Unknown Physical Parameters from Oscillating Time Series. CoRR (2021)
Julia Siekiera, Stefan Kramer
Deep Unsupervised Identification of Selected SNPs between Adapted Populations on Pool-seq Data. CoRR (2021)
Julia Siekiera, Marius Köppel, Edwin Simpson, Kevin Stowe, Iryna Gurevych, Stefan Kramer
Ranking Creative Language Characteristics in Small Data Scenarios. CoRR (2020)
Sophie Burkhardt, Jannis Brugger, Nicolas Wagner, Zahra Ahmadi, Kristian Kersting, Stefan Kramer
Rule Extraction from Binary Neural Networks with Convolutional Rules for Model Validation. CoRR (2020)
Mattia Cerrato, Marius Köppel, Alexander Segner, Roberto Esposito, Stefan Kramer
Fair pairwise learning to rank. DSAA (2020)
Sophie Burkhardt, Julia Siekiera, Josua Glodde, Miguel A. Andrade-Navarro, Stefan Kramer
Towards Identifying Drug Side Effects from Social Media Using Active Learning andCrowd Sourcing. PSB (2020)
Hermann Kaindl, Stefan Kramer
Towards Probability-based Safety Verification of Systems with Components from Machine Learning. CoRR (2020)
Derian Boer, Stefan Kramer
Secure Sum Outperforms Homomorphic Encryption in (Current) Collaborative Deep Learning. CoRR (2020)
Atif Raza, Stefan Kramer
Accelerating pattern-based time series classification: a linear time and space string mining approach. Knowl. Inf. Syst. 62 (3) (2020)
Stefan Kramer
A Brief History of Learning Symbolic Higher-Level Representations from Data (And a Curious Look Forward). IJCAI (2020)
Sophie Burkhardt, Stefan Kramer
Decoupling Sparsity and Smoothness in the Dirichlet Variational Autoencoder Topic Model. J. Mach. Learn. Res. 20 (2019)
Lukas Pensel, Stefan Kramer
Forecast of Study Success in the STEM Disciplines Based Solely on Academic Records. PKDD/ECML Workshops (1) (2019)
Sophie Burkhardt, Stefan Kramer
Multi-label classification using stacked hierarchical Dirichlet processes with reduced sampling complexity. Knowl. Inf. Syst. 59 (1) (2019)
Zahra Ahmadi, Stefan Kramer
Modeling Multi-label Recurrence in Data Streams. ICBK (2019)
Sriparna Saha, Debanjan Sarkar, Stefan Kramer
Exploring Multi-Objective Optimization for Multi-Label Classifier Ensembles. CEC (2019)
Marius Köppel, Alexander Segner, Martin Wagener, Lukas Pensel, Andreas Karwath, Stefan Kramer
Pairwise Learning to Rank by Neural Networks Revisited: Reconstruction, Theoretical Analysis and Practical Performance. ECML/PKDD (3) (2019)
Marius Köppel, Alexander Segner, Martin Wagener, Lukas Pensel, Andreas Karwath, Stefan Kramer
Pairwise Learning to Rank by Neural Networks Revisited: Reconstruction, Theoretical Analysis and Practical Performance. CoRR (2019)
Sophie Burkhardt, Stefan Kramer
A Survey of Multi-Label Topic Models. SIGKDD Explor. 21 (2) (2019)
Julian Vexler, Stefan Kramer
Integrating LSTMs with Online Density Estimation for the Probabilistic Forecast of Energy Consumption. DS (2019)
Zahra Ahmadi, Stefan Kramer
Modeling recurring concepts in data streams: a graph-based framework. Knowl. Inf. Syst. 55 (1) (2018)
Zahra Ahmadi, Stefan Kramer
A label compression method for online multi-label classification. Pattern Recognit. Lett. 111 (2018)
Junming Shao, Qinli Yang, Zhong Zhang, Jinhu Liu, Stefan Kramer
Graph Clustering with Local Density-Cut. DASFAA (1) (2018)
Zahra Ahmadi, Peter Martens, Christopher Koch, Thomas Gottron, Stefan Kramer
Towards Bankruptcy Prediction: Deep Sentiment Mining to Detect Financial Distress from Business Management Reports. DSAA (2018)
Michael Geilke, Andreas Karwath, Eibe Frank, Stefan Kramer
Online estimation of discrete, continuous, and conditional joint densities using classifier chains. Data Min. Knowl. Discov. 32 (3) (2018)
Sophie Burkhardt, Stefan Kramer
Online multi-label dependency topic models for text classification. Mach. Learn. 107 (5) (2018)
Hermann Kaindl, Stefan Kramer, Ralph Hoch
An inductive learning perspective on automated generation of feature models from given product specifications. SPLC (2018)
Robin Kobus, Adrian Lamoth, André Müller, Christian Hundt, Stefan Kramer, Bertil Schmidt
cuBool: Bit-Parallel Boolean Matrix Factorization on CUDA-Enabled Accelerators. ICPADS (2018)
Sriparna Saha, Sayantan Mitra, Stefan Kramer
Exploring Multiobjective Optimization for Multiview Clustering. ACM Trans. Knowl. Discov. Data 12 (4) (2018)
Patrick Rehn, Zahra Ahmadi, Stefan Kramer
Forest of Normalized Trees: Fast and Accurate Density Estimation of Streaming Data. DSAA (2018)
Zahra Ahmadi, Stefan Kramer
Online Multi-Label Classification: A Label Compression Method. CoRR (2018)
Derian Boer, Zahra Ahmadi, Stefan Kramer
Privacy Preserving Client/Vertical-Servers Classification. MIDAS/PAP@PKDD/ECML (2018)
Sophie Burkhardt, Stefan Kramer
Multi-label Classification Using Stacked Hierarchical Dirichlet Processes with Reduced Sampling Complexity. ICBK (2017)
Zahra Ahmadi, Aleksandrs Stier, Marcin Skowron, Stefan Kramer
To Parse or Not to Parse: An Experimental Comparison of RNTNs and CNNs for Sentiment Analysis. EMSASW@ESWC (2017)
Andreas Karwath, Markus Hubrich, Stefan Kramer
Convolutional Neural Networks for the Identification of Regions of Interest in PET Scans: A Study of Representation Learning for Diagnosing Alzheimer's Disease. AIME (2017)
Jörg Wicker, Stefan Kramer
The best privacy defense is a good privacy offense: obfuscating a search engine user's profile. Data Min. Knowl. Discov. 31 (5) (2017)
Atif Raza, Stefan Kramer
Ensembles of Randomized Time Series Shapelets Provide Improved Accuracy while Reducing Computational Costs. CoRR (2017)
Sophie Burkhardt, Stefan Kramer
Online Sparse Collapsed Hybrid Variational-Gibbs Algorithm for Hierarchical Dirichlet Process Topic Models. ECML/PKDD (2) (2017)
Zahra Ahmadi, Marcin Skowron, Aleksandrs Stier, Stefan Kramer
An In-Depth Experimental Comparison of RNTNs and CNNs for Sentence Modeling. DS (2017)
Michael Geilke, Stefan Kramer
Privacy-Preserving Pattern Mining on Online Density Estimates. ICBK (2017)
Jörg Wicker, Tim Lorsbach, Martin Gütlein, Emanuel Schmid, Diogo Latino, Stefan Kramer, Kathrin Fenner
enviPath - The environmental contaminant biotransformation pathway resource. Nucleic Acids Res. 44 (Database-Issue) (2016)
Jörg Wicker, Andrey Tyukin, Stefan Kramer
A Nonlinear Label Compression and Transformation Method for Multi-label Classification Using Autoencoders. PAKDD (1) (2016)
Junming Shao, Qinli Yang, Hoang-Vu Dang, Bertil Schmidt, Stefan Kramer
Scalable Clustering by Iterative Partitioning and Point Attractor Representation. ACM Trans. Knowl. Discov. Data 11 (1) (2016)
Junming Shao, Qinli Yang, Jinhu Liu, Stefan Kramer
Graph Clustering with Density-Cut. CoRR (2016)
Atif Raza, Jörg Wicker, Stefan Kramer
Trading off accuracy for efficiency by randomized greedy warping. SAC (2016)
Martin Gütlein, Stefan Kramer
Filtered circular fingerprints improve either prediction or runtime performance while retaining interpretability. J. Cheminformatics 8 (1) (2016)
Michael Geilke, Andreas Karwath, Stefan Kramer
Online Density Estimation of Heterogeneous Data Streams in Higher Dimensions. ECML/PKDD (1) (2016)
Jörg Wicker, Nicolas Krauter, Bettina Derstorff, Christof Stönner, Efstratios Bourtsoukidis, Thomas Klüpfel, Jonathan Williams, Stefan Kramer
Cinema Data Mining: The Smell of Fear. KDD (2015)
Sophie Burkhardt, Stefan Kramer
On the spectrum between binary relevance and classifier chains in multi-label classification. SAC (2015)
Eibe Frank, Michael Mayo, Stefan Kramer
Alternating model trees. SAC (2015)
Michael Geilke, Andreas Karwath, Stefan Kramer
Modeling recurrent distributions in streams using possible worlds. DSAA (2015)
Rui Li, Robert Perneczky, Alexander Drzezga, Stefan Kramer
Efficient redundancy reduced subgroup discovery via quadratic programming. J. Intell. Inf. Syst. 44 (2) (2015)
Andrey Tyukin, Stefan Kramer, Jörg Wicker
Scavenger - A Framework for Efficient Evaluation of Dynamic and Modular Algorithms. ECML/PKDD (3) (2015)
Jana Schmidt, Stefan Kramer
Online Induction of Probabilistic Real-Time Automata. J. Comput. Sci. Technol. 29 (3) (2014)
Andreas Hapfelmeier, Bernhard Pfahringer, Stefan Kramer
Pruning Incremental Linear Model Trees with Approximate Lookahead. IEEE Trans. Knowl. Data Eng. 26 (8) (2014)
Junming Shao, Zahra Ahmadi, Stefan Kramer
Prototype-based learning on concept-drifting data streams. KDD (2014)
Martin Gütlein, Andreas Karwath, Stefan Kramer
CheS-Mapper 2.0 for visual validation of (Q)SAR models. J. Cheminformatics 6 (1) (2014)
Rui Li, Zahra Ahmadi, Stefan Kramer
Constrained Latent Dirichlet Allocation for Subgroup Discovery with Topic Rules. ECAI (2014)
Michael Geilke, Andreas Karwath, Stefan Kramer
A probabilistic condensed representation of data for stream mining. DSAA (2014)
Madeleine Seeland, Andreas Maunz, Andreas Karwath, Stefan Kramer
Extracting information from support vector machines for pattern-based classification. SAC (2014)
Andrey Tyukin, Stefan Kramer, Jörg Wicker
BMaD - A Boolean Matrix Decomposition Framework. ECML/PKDD (3) (2014)
Madeleine Seeland, Andreas Karwath, Stefan Kramer
Structural clustering of millions of molecular graphs. SAC (2014)
Tobias Girschick, Lucia Puchbauer, Stefan Kramer
Improving structural similarity based virtual screening using background knowledge. J. Cheminformatics 5 (2013)
Jana Schmidt, Asghar Ghorbani, Andreas Hapfelmeier, Stefan Kramer
Learning probabilistic real-time automata from multi-attribute event logs. Intell. Data Anal. 17 (1) (2013)
Tobias Girschick, Ulrich Rückert, Stefan Kramer
Adapted Transfer of Distance Measures for Quantitative Structure-Activity Relationships and Data-Driven Selection of Source Datasets. Comput. J. 56 (3) (2013)
Madeleine Seeland, Stefan Kramer, Bernhard Pfahringer
Model selection based product kernel learning for regression on graphs. SAC (2013)
Michael Geilke, Eibe Frank, Andreas Karwath, Stefan Kramer
Online Estimation of Discrete Densities. ICDM (2013)
Andreas Hapfelmeier, Jana Schmidt, Stefan Kramer
Incremental linear model trees on massive datasets: keep it simple, keep it fast. SAC (2013)
Tobias Girschick, Pedro R. Almeida, Stefan Kramer, Jonna C. Stålring
Similarity Boosted Quantitative Structure-Activity Relationship - A Systematic Study of Enhancing Structural Descriptors by Molecular Similarity. J. Chem. Inf. Model. 53 (5) (2013)
Martin Gütlein, Andreas Karwath, Stefan Kramer
CheS-Mapper - Chemical Space Mapping and Visualization in 3D. J. Cheminformatics 4 (2012)
Jana Schmidt, Sonja Ansorge, Stefan Kramer
Scalable Induction of Probabilistic Real-Time Automata Using Maximum Frequent Pattern Based Clustering. SDM (2012)
Madeleine Seeland, Andreas Karwath, Stefan Kramer
A structural cluster kernel for learning on graphs. KDD (2012)
Madeleine Seeland, Fabian Buchwald, Stefan Kramer, Bernhard Pfahringer
Maximum Common Subgraph based locally weighted regression. SAC (2012)
Rui Li, Stefan Kramer
Efficient Redundancy Reduced Subgroup Discovery via Quadratic Programming. Discovery Science (2012)
Jana Schmidt, Stefan Kramer
Online Induction of Probabilistic Real Time Automata. ICDM (2012)
Zejun Zheng, Stefan Kramer, Bertil Schmidt
DySC: software for greedy clustering of 16S rRNA reads. Bioinform. 28 (16) (2012)
Jörg Wicker, Bernhard Pfahringer, Stefan Kramer
Multi-label classification using boolean matrix decomposition. SAC (2012)
Jana Schmidt, Stefan Kramer
The Augmented Itemset Tree: A Data Structure for Online Maximum Frequent Pattern Mining. Discovery Science (2011)
Andreas Maunz, Christoph Helma, Stefan Kramer
Efficient mining for structurally diverse subgraph patterns in large molecular databases. Mach. Learn. 83 (2) (2011)

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Publication Activity (10 Years)

Top Topics

Top Venues

Stefan Kramer