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Stefan Kramer 0001
Person information
- affiliation: Johannes Gutenberg University Mainz, Institute of Computer Science, Germany
Other persons with the same name
- Stefan Kramer — disambiguation page
- Stefan Kramer 0002 — Daimler AG, Germany
- Stefan Kramer 0003 — TU Berlin, Germany
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2020 – today
- 2024
- [c116]Cedric Derstroff, Mattia Cerrato, Jannis Brugger, Jan Peters, Stefan Kramer:
Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations. AAAI 2024: 11766-11774 - [c115]Kirsten Köbschall, Lisa Hartung
, Stefan Kramer
:
Soft Hoeffding Tree: A Transparent and Differentiable Model on Data Streams. DS 2024: 167-182 - [c114]Mattia Cerrato, Nicholas Schmitt, Lennart Baur, Edward Finkelstein, Selina Jukic, Lars Münzel, Felix Peter Paul, Pascal Pfannes, Benedikt Rohr, Julius Schellenberg, Philipp Wolf, Stefan Kramer:
Science-Gym: A Simple Testbed for AI-Driven Scientific Discovery. DS 2024: 229-243 - [i25]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 abs/2402.08511 (2024) - [i24]Mattia Cerrato, Marius Köppel, Philipp Wolf, Stefan Kramer:
10 Years of Fair Representations: Challenges and Opportunities. CoRR abs/2407.03834 (2024) - [i23]Derian Boer, Fabian Koch, Stefan Kramer:
Harnessing the Power of Semi-Structured Knowledge and LLMs with Triplet-Based Prefiltering for Question Answering. CoRR abs/2409.00861 (2024) - [i22]Kirsten Köbschall, Lisa Hartung, Stefan Kramer:
Soft Hoeffding Tree: A Transparent and Differentiable Model on Data Streams. CoRR abs/2411.04812 (2024) - 2023
- [c113]Mattia Cerrato, Marius Köppel, Roberto Esposito, Stefan Kramer:
Invariant Representations with Stochastically Quantized Neural Networks. AAAI 2023: 6962-6970 - [c112]Lukas-Malte Bammert, Stefan Kramer, Mattia Cerrato, Ernst Althaus:
Privacy-Preserving Learning of Random Forests Without Revealing the Trees. DS 2023: 372-386 - [c111]Julian Vexler
, Stefan Kramer
:
Classifying Aircraft Categories from Magnetometry Data Using a Hypotheses-Based Multi-Task Framework. ECAI 2023: 3241-3248 - [c110]Julian Vexler
, Stefan Kramer:
Identifying Aircraft Motions and Patterns from Magnetometry Data Using a Knowledge-Based Multi-Fusion Approach. FUSION 2023: 1-8 - [i21]Stefan Kramer, Mattia Cerrato, Saso Dzeroski, Ross D. King:
Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems. CoRR abs/2305.02251 (2023) - [i20]Cedric Derstroff, Mattia Cerrato, Jannis Brugger, Jan Peters, Stefan Kramer:
Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations. CoRR abs/2312.09950 (2023) - 2022
- [c109]Julia Siekiera, Marius Köppel, Edwin Simpson, Kevin Stowe, Iryna Gurevych, Stefan Kramer:
Ranking Creative Language Characteristics in Small Data Scenarios. ICCC 2022: 136-140 - [i19]Mattia Cerrato, Marius Köppel, Alexander Segner, Stefan Kramer:
Fair Group-Shared Representations with Normalizing Flows. CoRR abs/2201.06336 (2022) - [i18]Mattia Cerrato, Marius Köppel, Alexander Segner, Stefan Kramer:
Fair Interpretable Learning via Correction Vectors. CoRR abs/2201.06343 (2022) - [i17]Mattia Cerrato, Alesia Vallenas Coronel, Marius Köppel, Alexander Segner, Roberto Esposito, Stefan Kramer:
Fair Interpretable Representation Learning with Correction Vectors. CoRR abs/2202.03078 (2022) - [i16]Mattia Cerrato, Marius Köppel, Roberto Esposito
, Stefan Kramer:
Invariant Representations with Stochastically Quantized Neural Networks. CoRR abs/2208.02656 (2022) - [i15]Lukas Pensel, Stefan Kramer:
Neural RELAGGS. CoRR abs/2211.02363 (2022) - 2021
- [j48]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: 642263 (2021) - [c108]Stefan Kramer:
Myths and Misconceptions about Machine Learning and How They Are Related to Software Engineering. ENASE 2021: 5 - [c107]Weichen Li, Patrick Abels, Zahra Ahmadi
, Sophie Burkhardt, Benjamin Schiller, Iryna Gurevych, Stefan Kramer:
Topic-Guided Knowledge Graph Construction for Argument Mining. ICBK 2021: 315-322 - [c106]Stefan Kramer:
Myths and Misconceptions about Machine Learning and How They Are Related to Software Engineering. ICEIS (1) 2021: 7 - [e5]Nuria Oliver
, Fernando Pérez-Cruz
, Stefan Kramer, Jesse Read
, José Antonio Lozano
:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part I. Lecture Notes in Computer Science 12975, Springer 2021, ISBN 978-3-030-86485-9 [contents] - [e4]Nuria Oliver
, Fernando Pérez-Cruz
, Stefan Kramer, Jesse Read
, José Antonio Lozano
:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part II. Lecture Notes in Computer Science 12976, Springer 2021, ISBN 978-3-030-86519-1 [contents] - [e3]Nuria Oliver
, Fernando Pérez-Cruz
, Stefan Kramer, Jesse Read
, José Antonio Lozano
:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part III. Lecture Notes in Computer Science 12977, Springer 2021, ISBN 978-3-030-86522-1 [contents] - [i14]Julia Siekiera, Stefan Kramer:
Deep Unsupervised Identification of Selected SNPs between Adapted Populations on Pool-seq Data. CoRR abs/2101.00004 (2021) - [i13]Antoine Garcon, Julian Vexler
, Dmitry Budker, Stefan Kramer:
Deep Neural Networks to Recover Unknown Physical Parameters from Oscillating Time Series. CoRR abs/2101.03850 (2021) - [i12]Patrick Abels, Zahra Ahmadi, Sophie Burkhardt, Benjamin Schiller, Iryna Gurevych, Stefan Kramer:
Focusing Knowledge-based Graph Argument Mining via Topic Modeling. CoRR abs/2102.02086 (2021) - [i11]Atif Raza
, Stefan Kramer:
Pattern Sampling for Shapelet-based Time Series Classification. CoRR abs/2102.08498 (2021) - [i10]Ernst Althaus, Mohammad Sadeq Dousti, Stefan Kramer:
Fast Private Parameter Learning and Evaluation for Sum-Product Networks. CoRR abs/2104.07353 (2021) - 2020
- [j47]Atif Raza
, Stefan Kramer:
Accelerating pattern-based time series classification: a linear time and space string mining approach. Knowl. Inf. Syst. 62(3): 1113-1141 (2020) - [c105]Mattia Cerrato, Marius Köppel, Alexander Segner, Roberto Esposito
, Stefan Kramer:
Fair pairwise learning to rank. DSAA 2020: 729-738 - [c104]Stefan Kramer:
A Brief History of Learning Symbolic Higher-Level Representations from Data (And a Curious Look Forward). IJCAI 2020: 4868-4876 - [c103]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: 319-330 - [i9]Hermann Kaindl, Stefan Kramer:
Towards Probability-based Safety Verification of Systems with Components from Machine Learning. CoRR abs/2003.01155 (2020) - [i8]Derian Boer, Stefan Kramer:
Secure Sum Outperforms Homomorphic Encryption in (Current) Collaborative Deep Learning. CoRR abs/2006.02894 (2020) - [i7]Julia Siekiera, Marius Köppel, Edwin Simpson, Kevin Stowe, Iryna Gurevych, Stefan Kramer:
Ranking Creative Language Characteristics in Small Data Scenarios. CoRR abs/2010.12613 (2020) - [i6]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 abs/2012.08459 (2020)
2010 – 2019
- 2019
- [j46]Sophie Burkhardt, Stefan Kramer:
Decoupling Sparsity and Smoothness in the Dirichlet Variational Autoencoder Topic Model. J. Mach. Learn. Res. 20: 131:1-131:27 (2019) - [j45]Sophie Burkhardt
, Stefan Kramer:
Multi-label classification using stacked hierarchical Dirichlet processes with reduced sampling complexity. Knowl. Inf. Syst. 59(1): 93-115 (2019) - [j44]Sophie Burkhardt, Stefan Kramer:
A Survey of Multi-Label Topic Models. SIGKDD Explor. 21(2): 61-79 (2019) - [c102]Sriparna Saha, Debanjan Sarkar, Stefan Kramer:
Exploring Multi-Objective Optimization for Multi-Label Classifier Ensembles. CEC 2019: 2753-2760 - [c101]Julian Vexler
, Stefan Kramer
:
Integrating LSTMs with Online Density Estimation for the Probabilistic Forecast of Energy Consumption. DS 2019: 533-543 - [c100]Zahra Ahmadi
, Stefan Kramer:
Modeling Multi-label Recurrence in Data Streams. ICBK 2019: 9-16 - [c99]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: 237-252 - [c98]Lukas Pensel, Stefan Kramer:
Forecast of Study Success in the STEM Disciplines Based Solely on Academic Records. PKDD/ECML Workshops (1) 2019: 647-657 - [e2]Carlos Alzate, Anna Monreale, Haytham Assem, Albert Bifet, Teodora Sandra Buda, Bora Caglayan, Brett Drury, Eva García-Martín, Ricard Gavaldà, Stefan Kramer, Niklas Lavesson, Michael Madden, Ian M. Molloy, Maria-Irina Nicolae, Mathieu Sinn:
ECML PKDD 2018 Workshops - Nemesis 2018, UrbReas 2018, SoGood 2018, IWAISe 2018, and Green Data Mining 2018, Dublin, Ireland, September 10-14, 2018, Proceedings. Lecture Notes in Computer Science 11329, Springer 2019, ISBN 978-3-030-13452-5 [contents] - [i5]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 abs/1909.02768 (2019) - 2018
- [j43]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): 561-603 (2018) - [j42]Zahra Ahmadi
, Stefan Kramer:
Modeling recurring concepts in data streams: a graph-based framework. Knowl. Inf. Syst. 55(1): 15-44 (2018) - [j41]Sophie Burkhardt
, Stefan Kramer:
Online multi-label dependency topic models for text classification. Mach. Learn. 107(5): 859-886 (2018) - [j40]Zahra Ahmadi
, Stefan Kramer:
A label compression method for online multi-label classification. Pattern Recognit. Lett. 111: 64-71 (2018) - [j39]Sriparna Saha, Sayantan Mitra
, Stefan Kramer:
Exploring Multiobjective Optimization for Multiview Clustering. ACM Trans. Knowl. Discov. Data 12(4): 44:1-44:30 (2018) - [c97]Junming Shao, Qinli Yang, Zhong Zhang
, Jinhu Liu, Stefan Kramer:
Graph Clustering with Local Density-Cut. DASFAA (1) 2018: 187-202 - [c96]Patrick Rehn, Zahra Ahmadi
, Stefan Kramer:
Forest of Normalized Trees: Fast and Accurate Density Estimation of Streaming Data. DSAA 2018: 199-208 - [c95]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: 293-302 - [c94]Robin Kobus, Adrian Lamoth, André Müller
, Christian Hundt, Stefan Kramer, Bertil Schmidt:
cuBool: Bit-Parallel Boolean Matrix Factorization on CUDA-Enabled Accelerators. ICPADS 2018: 465-472 - [c93]Derian Boer, Zahra Ahmadi
, Stefan Kramer:
Privacy Preserving Client/Vertical-Servers Classification. MIDAS/PAP@PKDD/ECML 2018: 125-140 - [c92]Hermann Kaindl, Stefan Kramer, Ralph Hoch:
An inductive learning perspective on automated generation of feature models from given product specifications. SPLC 2018: 25-30 - [i4]Zahra Ahmadi, Stefan Kramer:
Online Multi-Label Classification: A Label Compression Method. CoRR abs/1804.01491 (2018) - 2017
- [j38]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): 1419-1443 (2017) - [c91]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: 316-321 - [c90]Zahra Ahmadi
, Marcin Skowron, Aleksandrs Stier, Stefan Kramer:
An In-Depth Experimental Comparison of RNTNs and CNNs for Sentence Modeling. DS 2017: 144-152 - [c89]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 - [c88]Sophie Burkhardt, Stefan Kramer:
Multi-label Classification Using Stacked Hierarchical Dirichlet Processes with Reduced Sampling Complexity. ICBK 2017: 1-8 - [c87]Michael Geilke, Stefan Kramer:
Privacy-Preserving Pattern Mining on Online Density Estimates. ICBK 2017: 25-32 - [c86]Sophie Burkhardt, Stefan Kramer:
Online Sparse Collapsed Hybrid Variational-Gibbs Algorithm for Hierarchical Dirichlet Process Topic Models. ECML/PKDD (2) 2017: 189-204 - [r2]Stefan Kramer:
Inductive Database Approach to Graphmining. Encyclopedia of Machine Learning and Data Mining 2017: 641-642 - [i3]Atif Raza
, Stefan Kramer:
Ensembles of Randomized Time Series Shapelets Provide Improved Accuracy while Reducing Computational Costs. CoRR abs/1702.06712 (2017) - 2016
- [j37]Martin Gütlein
, Stefan Kramer:
Filtered circular fingerprints improve either prediction or runtime performance while retaining interpretability. J. Cheminformatics 8(1): 60:1-60:16 (2016) - [j36]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): 502-508 (2016) - [j35]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): 5:1-5:23 (2016) - [c85]Jörg Wicker
, Andrey Tyukin, Stefan Kramer:
A Nonlinear Label Compression and Transformation Method for Multi-label Classification Using Autoencoders. PAKDD (1) 2016: 328-340 - [c84]Michael Geilke, Andreas Karwath
, Stefan Kramer:
Online Density Estimation of Heterogeneous Data Streams in Higher Dimensions. ECML/PKDD (1) 2016: 65-80 - [c83]Atif Raza
, Jörg Wicker
, Stefan Kramer:
Trading off accuracy for efficiency by randomized greedy warping. SAC 2016: 883-890 - [p2]Jörg Wicker
, Kathrin Fenner, Stefan Kramer:
A Hybrid Machine Learning and Knowledge Based Approach to Limit Combinatorial Explosion in Biodegradation Prediction. Computational Sustainability 2016: 75-97 - [i2]Junming Shao, Qinli Yang, Jinhu Liu, Stefan Kramer:
Graph Clustering with Density-Cut. CoRR abs/1606.00950 (2016) - 2015
- [j34]Rui Li, Robert Perneczky
, Alexander Drzezga
, Stefan Kramer:
Efficient redundancy reduced subgroup discovery via quadratic programming. J. Intell. Inf. Syst. 44(2): 271-288 (2015) - [c82]Michael Geilke, Andreas Karwath
, Stefan Kramer:
Modeling recurrent distributions in streams using possible worlds. DSAA 2015: 1-9 - [c81]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: 1295-1304 - [c80]Andrey Tyukin, Stefan Kramer, Jörg Wicker
:
Scavenger - A Framework for Efficient Evaluation of Dynamic and Modular Algorithms. ECML/PKDD (3) 2015: 325-328 - [c79]Eibe Frank
, Michael Mayo, Stefan Kramer:
Alternating model trees. SAC 2015: 871-878 - [c78]Sophie Burkhardt, Stefan Kramer:
On the spectrum between binary relevance and classifier chains in multi-label classification. SAC 2015: 885-892 - 2014
- [j33]Martin Gütlein, Andreas Karwath
, Stefan Kramer:
CheS-Mapper 2.0 for visual validation of (Q)SAR models. J. Cheminformatics 6(1): 41 (2014) - [j32]Jana Schmidt, Stefan Kramer:
Online Induction of Probabilistic Real-Time Automata. J. Comput. Sci. Technol. 29(3): 345-360 (2014) - [j31]Andreas Hapfelmeier, Bernhard Pfahringer, Stefan Kramer:
Pruning Incremental Linear Model Trees with Approximate Lookahead. IEEE Trans. Knowl. Data Eng. 26(8): 2072-2076 (2014) - [c77]Michael Geilke, Andreas Karwath
, Stefan Kramer:
A probabilistic condensed representation of data for stream mining. DSAA 2014: 297-303 - [c76]Rui Li, Zahra Ahmadi
, Stefan Kramer:
Constrained Latent Dirichlet Allocation for Subgroup Discovery with Topic Rules. ECAI 2014: 519-524 - [c75]Junming Shao, Zahra Ahmadi
, Stefan Kramer:
Prototype-based learning on concept-drifting data streams. KDD 2014: 412-421 - [c74]Andrey Tyukin, Stefan Kramer, Jörg Wicker
:
BMaD - A Boolean Matrix Decomposition Framework. ECML/PKDD (3) 2014: 481-484 - [c73]Madeleine Seeland, Andreas Karwath
, Stefan Kramer:
Structural clustering of millions of molecular graphs. SAC 2014: 121-128 - [c72]Madeleine Seeland, Andreas Maunz, Andreas Karwath
, Stefan Kramer:
Extracting information from support vector machines for pattern-based classification. SAC 2014: 129-136 - 2013
- [j30]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): 274-288 (2013) - [j29]Jana Schmidt, Asghar Ghorbani
, Andreas Hapfelmeier, Stefan Kramer:
Learning probabilistic real-time automata from multi-attribute event logs. Intell. Data Anal. 17(1): 93-123 (2013) - [j28]Tobias Girschick, Lucia Puchbauer, Stefan Kramer:
Improving structural similarity based virtual screening using background knowledge. J. Cheminformatics 5: 50 (2013) - [j27]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): 1017-1025 (2013) - [c71]Michael Geilke, Eibe Frank
, Andreas Karwath
, Stefan Kramer:
Online Estimation of Discrete Densities. ICDM 2013: 191-200 - [c70]Andreas Hapfelmeier, Jana Schmidt, Stefan Kramer:
Incremental linear model trees on massive datasets: keep it simple, keep it fast. SAC 2013: 129-135 - [c69]Madeleine Seeland, Stefan Kramer, Bernhard Pfahringer:
Model selection based product kernel learning for regression on graphs. SAC 2013: 136-143 - 2012
- [j26]Zejun Zheng, Stefan Kramer, Bertil Schmidt
:
DySC: software for greedy clustering of 16S rRNA reads. Bioinform. 28(16): 2182-2183 (2012) - [j25]Martin Gütlein, Andreas Karwath
, Stefan Kramer:
CheS-Mapper - Chemical Space Mapping and Visualization in 3D. J. Cheminformatics 4: 7 (2012) - [c68]Rui Li, Stefan Kramer:
Efficient Redundancy Reduced Subgroup Discovery via Quadratic Programming. Discovery Science 2012: 125-138 - [c67]Jana Schmidt, Stefan Kramer:
Online Induction of Probabilistic Real Time Automata. ICDM 2012: 625-634 - [c66]Madeleine Seeland, Andreas Karwath
, Stefan Kramer:
A structural cluster kernel for learning on graphs. KDD 2012: 516-524 - [c65]Madeleine Seeland, Fabian Buchwald, Stefan Kramer, Bernhard Pfahringer:
Maximum Common Subgraph based locally weighted regression. SAC 2012: 165-172 - [c64]Jörg Wicker
, Bernhard Pfahringer, Stefan Kramer:
Multi-label classification using boolean matrix decomposition. SAC 2012: 179-186 - [c63]Jana Schmidt, Sonja Ansorge, Stefan Kramer:
Scalable Induction of Probabilistic Real-Time Automata Using Maximum Frequent Pattern Based Clustering. SDM 2012: 272-283 - 2011
- [j24]Tobias Hamp, Fabian Birzele, Fabian Buchwald, Stefan Kramer:
Improving structure alignment-based prediction of SCOP families using Vorolign Kernels. Bioinform. 27(2): 204-210 (2011) - [j23]Fabian Buchwald, Lothar Richter, Stefan Kramer:
Predicting a small molecule-kinase interaction map: A machine learning approach. J. Cheminformatics 3: 22 (2011) - [j22]Andreas Maunz, Christoph Helma, Stefan Kramer:
Efficient mining for structurally diverse subgraph patterns in large molecular databases. Mach. Learn. 83(2): 193-218 (2011) - [c62]Rui Li, Andreas Hapfelmeier, Jana Schmidt, Robert Perneczky
, Alexander Drzezga
, Alexander Kurz, Stefan Kramer:
A Case Study of Stacked Multi-view Learning in Dementia Research. AIME 2011: 60-69 - [c61]Jana Schmidt, Stefan Kramer:
The Augmented Itemset Tree: A Data Structure for Online Maximum Frequent Pattern Mining. Discovery Science 2011: 277-291 - [c60]Jana Schmidt, Elisabeth Maria Brändle, Stefan Kramer:
Clustering with Attribute-Level Constraints. ICDM 2011: 1206-1211 - [c59]Madeleine Seeland, Simon A. Berger, Alexandros Stamatakis
, Stefan Kramer:
Parallel Structural Graph Clustering. ECML/PKDD (3) 2011: 256-272 - 2010
- [j21]