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ORCIDEmmanuel Müller
Emmanuel Alexander Müller
Person information
- affiliation: Technical University of Dortmund, Germany
- affiliation (former): Hasso Plattner Institute, Potsdam, Germany
- affiliation (former): Karlsruhe Institute of Technology, IPD, Germany
- affiliation (former): RWTH Aachen University, Germany
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2020 – today
- 2024
[j12]Bin Li
, Shubham Gupta, Emmanuel Müller:
State-transition-aware anomaly detection under concept drifts. Data Knowl. Eng. 154: 102365 (2024)- [c99]Chiara Balestra, Antonio Ferrara, Emmanuel Müller:
FairMC Fair-Markov Chain Rank Aggregation Methods. DaWaK 2024: 315-321 - [c98]Mohammad-Sahadet Hossain, Mohammad Sakhawat Hossain, Simon Klüttermann, Emmanuel Müller:
Evaluating Anomaly Detection Algorithms: A Multi-Metric Analysis Across Variable Class Imbalances. IJCNN 2024: 1-7 - [c97]Simon Klüttermann, Jérôme Rutinowski, Emmanuel Müller:
The Phenomenon of Correlated Representations in Contrastive Learning. IJCNN 2024: 1-8 - [c96]Vikas Kumar, Vishesh Srivastava, Sadia Mahjabin, Arindam Pal, Simon Klüttermann, Emmanuel Müller:
Autoencoder Optimization for Anomaly Detection: A Comparative Study with Shallow Algorithms. IJCNN 2024: 1-8 - [c95]Bin Li, Emmanuel Müller:
Cohesive Explanation for Time Series Prediction. IJCNN 2024: 1-9 - [c94]Simon Klüttermann, Chiara Balestra, Emmanuel Müller:
On the Efficient Explanation of Outlier Detection Ensembles Through Shapley Values. PAKDD (3) 2024: 43-55 - [c93]Jérôme Rutinowski, Simon Klüttermann, Jan Endendyk, Christopher Reining, Emmanuel Müller:
Benchmarking Trust: A Metric for Trustworthy Machine Learning. xAI (1) 2024: 287-307 - [e4]Zahraa S. Abdallah, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier, Matthias Jakobs, Emmanuel Müller, Maximilian Muschalik, Panagiotis Papapetrou, Amal Saadallah, George Tzagkarakis:
Proceedings of the Workshop on Explainable AI for Time Series and Data Streams (TempXAI 2024) co-located with The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2024), Vilnius, Lithuania, September 9th, 2024. CEUR Workshop Proceedings 3761, CEUR-WS.org 2024 [contents] - [i25]Simon Klüttermann, Jérôme Rutinowski, Anh Nguyen, Britta Grimme, Moritz Roidl, Emmanuel Müller:
On the Effectiveness of Heterogeneous Ensemble Methods for Re-identification. CoRR abs/2403.12606 (2024) - [i24]Simon Klüttermann, Emmanuel Müller:
About Test-time training for outlier detection. CoRR abs/2404.03495 (2024) - [i23]Chiara Balestra, Andreas Mayr, Emmanuel Müller:
Ranking evaluation metrics from a group-theoretic perspective. CoRR abs/2408.16009 (2024) - [i22]Minjae Ok, Simon Klüttermann, Emmanuel Müller:
Exploring the Impact of Outlier Variability on Anomaly Detection Evaluation Metrics. CoRR abs/2409.15986 (2024) - 2023
- [j11]Anton Tsitsulin, John Palowitch, Bryan Perozzi, Emmanuel Müller:
Graph Clustering with Graph Neural Networks. J. Mach. Learn. Res. 24: 127:1-127:21 (2023) - [c92]Magdalena Wischnewski, Nicole C. Krämer, Emmanuel Müller:
Measuring and Understanding Trust Calibrations for Automated Systems: A Survey of the State-Of-The-Art and Future Directions. CHI 2023: 755:1-755:16 - [c91]Arn Baudzus, Bin Li, Adnane Jadid, Emmanuel Müller:
On Model Performance Estimation in Time Series Anomaly Detection. CIIS 2023: 106-117 - [c90]Bin Li, Emmanuel Müller:
State-Transition-Aware Anomaly Detection Under Concept Drifts. DaWaK 2023: 49-63 - [c89]Gernot Schmitz, Daniel Wilmes, Alexander Gerharz, Daniel Horn, Emmanuel Müller:
Contextual Shift Method (CSM). DaWaK 2023: 101-106 - [c88]Lara Kuhlmann, Daniel Wilmes, Emmanuel Müller, Markus Pauly, Daniel Horn:
RODD: Robust Outlier Detection in Data Cubes. DaWaK 2023: 325-339 - [c87]Chiara Balestra, Bin Li, Emmanuel Müller:
slidSHAPs - sliding Shapley Values for correlation-based change detection in time series. DSAA 2023: 1-10 - [c86]Carina Newen, Emmanuel Müller:
On the Independence of Adversarial Transferability to Topological Changes in the Dataset. DSAA 2023: 1-8 - [c85]Simon Klüttermann, Jérôme Rutinowski, Anh Nguyen, Christopher Reining, Moritz Roidl, Emmanuel Müller:
On Graph Representation based Re-Identification - A Proof of Concept. ICDM (Workshops) 2023: 1097-1104 - [c84]Simon Klüttermann, Emmanuel Müller:
Evaluating and Comparing Heterogeneous Ensemble Methods for Unsupervised Anomaly Detection. IJCNN 2023: 1-8 - [c83]Bin Li, Emmanuel Müller:
Contrastive Time Series Anomaly Detection by Temporal Transformations. IJCNN 2023: 1-8 - [c82]Arn Baudzus, Bin Li, Adnane Jadid, Emmanuel Müller:
The Good, The Bad, and The Average: Benchmarking of Reconstruction Based Multivariate Time Series Anomaly Detection. ECML/PKDD (7) 2023: 356-360 - [i21]Lara Kuhlmann, Daniel Wilmes, Emmanuel Müller, Markus Pauly, Daniel Horn:
RODD: Robust Outlier Detection in Data Cubes. CoRR abs/2303.08193 (2023) - [i20]Simon Lutz, Florian Wittbold, Simon Dierl, Benedikt Böing, Falk Howar, Barbara König, Emmanuel Müller, Daniel Neider:
Interpretable Anomaly Detection via Discrete Optimization. CoRR abs/2303.14111 (2023) - [i19]Bin Li, Carsten Jentsch, Emmanuel Müller:
Prototypes as Explanation for Time Series Anomaly Detection. CoRR abs/2307.01601 (2023) - [i18]Chiara Balestra, Carlo Maj, Emmanuel Müller, Andreas Mayr:
Redundancy-aware unsupervised rankings for collections of gene sets. CoRR abs/2307.16182 (2023) - [i17]Chiara Balestra, Bin Li, Emmanuel Müller:
On the Consistency and Robustness of Saliency Explanations for Time Series Classification. CoRR abs/2309.01457 (2023) - 2022
- [c81]Benedikt Böing, Falk Howar, Jelle Hüntelmann, Emmanuel Müller, Richard Stewing:
Neural Network Verification with DSE. OVERLAY@AI*IA 2022: 1-6 - [c80]Chiara Balestra, Florian Huber, Andreas Mayr, Emmanuel Müller:
Unsupervised Features Ranking via Coalitional Game Theory for Categorical Data. DaWaK 2022: 97-111 - [c79]Benedikt Böing, Emmanuel Müller:
On Training and Verifying Robust Autoencoders. DSAA 2022: 1-10 - [c78]Carina Newen, Emmanuel Müller:
Unsupervised DeepView: Global Explainability of Uncertainties for High Dimensional Data. ICKG 2022: 196-202 - [c77]Carina Newen, Emmanuel Müller:
Unsupervised DeepView: Global Uncertainty Visualization for High Dimensional Data. ICDM (Workshops) 2022: 1-8 - [c76]Daniil Kaminskyi, Bin Li, Emmanuel Müller:
Reconstruction-based unsupervised drift detection over multivariate streaming data. ICDM (Workshops) 2022: 807-813 - [c75]Benedikt Böing, Simon Klüttermann, Emmanuel Müller:
Post-Robustifying Deep Anomaly Detection Ensembles by Model Selection. ICDM 2022: 861-866 - [c74]Simon Klüttermann, Jérôme Rutinowski, Christopher Reining, Moritz Roidl, Emmanuel Müller:
Towards Graph Representation based Re-Identification of Chipwood Pallet Blocks. ICMLA 2022: 1543-1550 - [c73]Benedikt Tobias Müller, Marvin Ender, Jan Erik Swiadek, Mengcheng Jin, Simon Winkel, Dominik Niedziela, Bin Li, Jelle Hüntelmann, Emmanuel Müller:
ADEPT: Anomaly Detection, Explanation and Processing for Time Series with a Focus on Energy Consumption Data. ECML/PKDD (6) 2022: 622-626 - [c72]Bin Li, Emmanuel Müller:
STAD: State-Transition-Aware Anomaly Detection Under Concept Drifts. OLUD@WCCI 2022 - [i16]Chiara Balestra, Florian Huber, Andreas Mayr, Emmanuel Müller:
Unsupervised Features Ranking via Coalitional Game Theory for Categorical Data. CoRR abs/2205.09060 (2022) - [i15]Chiara Balestra, Carlo Maj, Emmanuel Müller, Andreas Mayr:
Redundancy-aware unsupervised ranking based on game theory - application to gene enrichment analysis. CoRR abs/2207.12184 (2022) - [i14]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller:
Spectral Graph Complexity. CoRR abs/2211.01434 (2022) - 2021
- [j10]Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Ivan V. Oseledets, Emmanuel Müller:
FREDE: Anytime Graph Embeddings. Proc. VLDB Endow. 14(6): 1102-1110 (2021) - [c71]Benedikt Böing, Rajarshi Roy, Daniel Neider, Emmanuel Müller:
QUGA - Quality Guarantees for Autoencoders. OVERLAY@GandALF 2021: 103-107 - [c70]Erik Scharwächter, Jonathan Lennartz, Emmanuel Müller:
Differentiable Segmentation of Sequences. ICLR 2021 - 2020
- [c69]Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, Klaus-Robert Müller, Marius Kloft:
Deep Semi-Supervised Anomaly Detection. ICLR 2020 - [c68]Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Ivan V. Oseledets, Emmanuel Müller:
The Shape of Data: Intrinsic Distance for Data Distributions. ICLR 2020 - [c67]Benedikt Böing, Rajarshi Roy, Emmanuel Müller, Daniel Neider:
Quality Guarantees for Autoencoders via Unsupervised Adversarial Attacks. ECML/PKDD (2) 2020: 206-222 - [c66]Erik Scharwächter, Emmanuel Müller:
Two-Sample Testing for Event Impacts in Time Series. SDM 2020: 10-18 - [i13]Erik Scharwächter, Emmanuel Müller:
Does Terrorism Trigger Online Hate Speech? On the Association of Events and Time Series. CoRR abs/2004.14733 (2020) - [i12]Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Ivan V. Oseledets, Emmanuel Müller:
FREDE: Linear-Space Anytime Graph Embeddings. CoRR abs/2006.04746 (2020) - [i11]Erik Scharwächter, Jonathan Lennartz, Emmanuel Müller:
Differentiable Segmentation of Sequences. CoRR abs/2006.13105 (2020) - [i10]Anton Tsitsulin, John Palowitch, Bryan Perozzi, Emmanuel Müller:
Graph Clustering with Graph Neural Networks. CoRR abs/2006.16904 (2020) - [i9]Erik Scharwächter, Emmanuel Müller:
Statistical Evaluation of Anomaly Detectors for Sequences. CoRR abs/2008.05788 (2020)
2010 – 2019
- 2019
- [c65]Tara Safavi, Caleb Belth, Lukas Faber, Davide Mottin, Emmanuel Müller, Danai Koutra:
Personalized Knowledge Graph Summarization: From the Cloud to Your Pocket. ICDM 2019: 528-537 - [c64]Nikita Klyuchnikov, Davide Mottin, Georgia Koutrika, Emmanuel Müller, Panagiotis Karras:
Figuring out the User in a Few Steps: Bayesian Multifidelity Active Search with Cokriging. KDD 2019: 686-695 - [c63]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller:
Spectral Graph Complexity. WWW (Companion Volume) 2019: 308-309 - [i8]Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Ivan V. Oseledets, Emmanuel Müller:
Intrinsic Multi-scale Evaluation of Generative Models. CoRR abs/1905.11141 (2019) - [i7]Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, Klaus-Robert Müller, Marius Kloft:
Deep Semi-Supervised Anomaly Detection. CoRR abs/1906.02694 (2019) - 2018
- [c62]Arvind Kumar Shekar, Marcus Pappik, Patricia Iglesias Sánchez, Emmanuel Müller:
Selection of Relevant and Non-Redundant Multivariate Ordinal Patterns for Time Series Classification. DS 2018: 224-240 - [c61]Davide Mottin, Bastian Grasnick, Axel Kroschk, Patrick Siegler, Emmanuel Müller:
Notable Characteristics Search through Knowledge Graphs. EDBT 2018: 429-432 - [c60]Lukas Ruff, Nico Görnitz, Lucas Deecke, Shoaib Ahmed Siddiqui, Robert A. Vandermeulen, Alexander Binder, Emmanuel Müller, Marius Kloft:
Deep One-Class Classification. ICML 2018: 4390-4399 - [c59]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller:
NetLSD: Hearing the Shape of a Graph. KDD 2018: 2347-2356 - [c58]Erik Scharwächter, Fabian Geier, Lukas Faber, Emmanuel Müller:
Low Redundancy Estimation of Correlation Matrices for Time Series Using Triangular Bounds. PAKDD (2) 2018: 458-470 - [c57]Freya Behrens, Sebastian Bischoff, Pius Ladenburger, Julius Rückin, Laurenz Seidel, Fabian Stolp, Michael Vaichenker, Adrian Ziegler, Davide Mottin, Fatemeh Aghaei, Emmanuel Müller, Martin Preusse, Nikola Müller, Michael Hunger:
MetaExp: Interactive Explanation and Exploration of Large Knowledge Graphs. WWW (Companion Volume) 2018: 199-202 - [c56]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Emmanuel Müller:
VERSE: Versatile Graph Embeddings from Similarity Measures. WWW 2018: 539-548 - [i6]Davide Mottin, Bastian Grasnick, Axel Kroschk, Patrick Siegler, Emmanuel Müller:
Notable Characteristics Search through Knowledge Graphs. CoRR abs/1802.04060 (2018) - [i5]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Emmanuel Müller:
VERSE: Versatile Graph Embeddings from Similarity Measures. CoRR abs/1803.04742 (2018) - [i4]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller:
NetLSD: Hearing the Shape of a Graph. CoRR abs/1805.10712 (2018) - [i3]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller:
SGR: Self-Supervised Spectral Graph Representation Learning. CoRR abs/1811.06237 (2018) - 2017
- [c55]Fabian Maschler, Fabian Geier, Bodo Bookhagen, Emmanuel Müller:
Locality-Based Graph Clustering of Spatially Embedded Time Series. COMPLEX NETWORKS 2017: 719-730 - [c54]Arvind Kumar Shekar, Patricia Iglesias Sánchez, Emmanuel Müller:
Diverse Selection of Feature Subsets for Ensemble Regression. DaWaK 2017: 259-273 - [c53]Arvind Kumar Shekar, Tom Bocklisch, Patricia Iglesias Sánchez, Christoph Nikolas Straehle, Emmanuel Müller:
Including Multi-feature Interactions and Redundancy for Feature Ranking in Mixed Datasets. ECML/PKDD (1) 2017: 239-255 - [c52]Louis Kirsch, Niklas Riekenbrauck, Daniel Thevessen, Marcus Pappik, Axel Stebner, Julius Kunze, Alexander Meissner, Arvind Kumar Shekar, Emmanuel Müller:
Framework for Exploring and Understanding Multivariate Correlations. ECML/PKDD (3) 2017: 404-408 - [c51]Davide Mottin, Emmanuel Müller:
Graph Exploration: From Users to Large Graphs. SIGMOD Conference 2017: 1737-1740 - 2016
- [c50]Thomas Van Brussel, Emmanuel Müller, Bart Goethals:
Discovering Overlapping Quantitative Associations by Density-Based Mining of Relevant Attributes. FoIKS 2016: 131-148 - [c49]Andranik Khachatryan, Emmanuel Müller, Klemens Böhm, Christian Stier:
Improving accuracy and robustness of self-tuning histograms by subspace clustering. ICDE 2016: 1544-1545 - [c48]Erik Scharwächter, Emmanuel Müller, Jonathan F. Donges, Marwan Hassani, Thomas Seidl:
Detecting Change Processes in Dynamic Networks by Frequent Graph Evolution Rule Mining. ICDM 2016: 1191-1196 - [e3]Ralf Krestel, Davide Mottin, Emmanuel Müller:
Proceedings of the Conference "Lernen, Wissen, Daten, Analysen", Potsdam, Germany, September 12-14, 2016. CEUR Workshop Proceedings 1670, CEUR-WS.org 2016 [contents] - 2015
- [j9]Hoang Vu Nguyen, Emmanuel Müller, Jilles Vreeken, Klemens Böhm:
Erratum to: Unsupervised interaction-preserving discretization of multivariate data. Data Min. Knowl. Discov. 29(1): 296-297 (2015) - [j8]Emmanuel Müller, Ira Assent, Stephan Günnemann, Thomas Seidl, Jennifer G. Dy:
MultiClust special issue on discovering, summarizing and using multiple clusterings. Mach. Learn. 98(1-2): 1-5 (2015) - [j7]Andranik Khachatryan, Emmanuel Müller, Christian Stier, Klemens Böhm:
Improving Accuracy and Robustness of Self-Tuning Histograms by Subspace Clustering. IEEE Trans. Knowl. Data Eng. 27(9): 2377-2389 (2015) - [c47]Thibault Sellam, Emmanuel Müller, Martin L. Kersten:
Semi-Automated Exploration of Data Warehouses. CIKM 2015: 1321-1330 - [c46]Emin Aksehirli, Bart Goethals, Emmanuel Müller:
Efficient Cluster Detection by Ordered Neighborhoods. DaWaK 2015: 15-27 - [c45]Hoang Vu Nguyen, Klemens Böhm, Florian Becker, Bertrand Goldman, Georg Hinkel, Emmanuel Müller:
Identifying User Interests within the Data Space - a Case Study with SkyServer. EDBT 2015: 641-652 - [c44]Patricia Iglesias Sánchez, Emmanuel Müller, Uwe Leo Korn, Klemens Böhm, Andrea Kappes, Tanja Hartmann, Dorothea Wagner:
Efficient Algorithms for a Robust Modularity-Driven Clustering of Attributed Graphs. SDM 2015: 100-108 - [c43]Emmanuel Müller:
Keynote abstract: Subspace search for community detection and community outlier mining in attributed graphs. SMAP 2015: xvii - [c42]Fabian Keller, Emmanuel Müller, Klemens Böhm:
Estimating mutual information on data streams. SSDBM 2015: 3:1-3:12 - 2014
- [j6]Hoang Vu Nguyen, Emmanuel Müller, Klemens Böhm:
A Near-Linear Time Subspace Search Scheme for Unsupervised Selection of Correlated Features. Big Data Res. 1: 37-51 (2014) - [j5]Hoang Vu Nguyen, Emmanuel Müller, Jilles Vreeken, Klemens Böhm:
Unsupervised interaction-preserving discretization of multivariate data. Data Min. Knowl. Discov. 28(5-6): 1366-1397 (2014) - [c41]Hoang Vu Nguyen, Emmanuel Müller, Jilles Vreeken, Pavel Efros, Klemens Böhm:
Multivariate Maximal Correlation Analysis. ICML 2014: 775-783 - [c40]Bryan Perozzi, Leman Akoglu, Patricia Iglesias Sánchez, Emmanuel Müller:
Focused clustering and outlier detection in large attributed graphs. KDD 2014: 1346-1355 - [c39]Emmanuel Müller:
Subspace Search for Community Detection and Community Outlier Mining in Attributed Graphs. LWA 2014: 109-110 - [c38]Patricia Iglesias Sánchez, Emmanuel Müller, Oretta Irmler, Klemens Böhm:
Local context selection for outlier ranking in graphs with multiple numeric node attributes. SSDBM 2014: 16:1-16:12 - [c37]Hoang Vu Nguyen, Emmanuel Müller, Periklis Andritsos, Klemens Böhm:
Detecting correlated columns in relational databases with mixed data types. SSDBM 2014: 30:1-30:12 - 2013
- [c36]Hoang Vu Nguyen, Emmanuel Müller, Klemens Böhm:
4S: Scalable subspace search scheme overcoming traditional Apriori processing. IEEE BigData 2013: 359-367 - [c35]Fabian Keller, Emmanuel Müller, Andreas Wixler, Klemens Böhm:
Flexible and adaptive subspace search for outlier analysis. CIKM 2013: 1381-1390 - [c34]Emmanuel Müller, Patricia Iglesias Sánchez, Yvonne Mülle, Klemens Böhm:
Ranking outlier nodes in subspaces of attributed graphs. ICDE Workshops 2013: 216-222 - [c33]Patricia Iglesias Sánchez, Emmanuel Müller, Fabian Laforet, Fabian Keller, Klemens Böhm:
Statistical Selection of Congruent Subspaces for Mining Attributed Graphs. ICDM 2013: 647-656 - [c32]Emin Aksehirli, Bart Goethals, Emmanuel Müller, Jilles Vreeken:
Cartification: A Neighborhood Preserving Transformation for Mining High Dimensional Data. ICDM 2013: 937-942 - [c31]Emmanuel Müller:
Flexible Subspace Search for Outlier Detection and Description. LWA 2013: 121 - [c30]Klemens Böhm, Fabian Keller, Emmanuel Müller, Hoang Vu Nguyen, Jilles Vreeken:
CMI: An Information-Theoretic Contrast Measure for Enhancing Subspace Cluster and Outlier Detection. SDM 2013: 198-206 - 2012
- [c29]Fabian Keller, Emmanuel Müller, Klemens Böhm:
HiCS: High Contrast Subspaces for Density-Based Outlier Ranking. ICDE 2012: 1037-1048 - [c28]Emmanuel Müller, Stephan Günnemann, Ines Färber, Thomas Seidl:
Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data. ICDE 2012: 1207-1210 - [c27]Emmanuel Müller, Ira Assent, Patricia Iglesias Sánchez, Yvonne Mülle, Klemens Böhm:
Outlier Ranking via Subspace Analysis in Multiple Views of the Data. ICDM 2012: 529-538 - [c26]Emmanuel Müller, Fabian Keller, Sebastian Blanc, Klemens Böhm:
OutRules: A Framework for Outlier Descriptions in Multiple Context Spaces. ECML/PKDD (2) 2012: 828-832 - [c25]Andranik Khachatryan, Emmanuel Müller, Christian Stier, Klemens Böhm:
Sensitivity of Self-tuning Histograms: Query Order Affecting Accuracy and Robustness. SSDBM 2012: 334-342 - [e2]Emmanuel Müller, Thomas Seidl, Suresh Venkatasubramanian, Arthur Zimek:
3rd MultiClust Workshop: Discovering, Summarizing and Using Multiple Clusterings, MultiClust '12, in conjunction with SDM 2012, Anaheim, CA, USA, April 28, 2012, Anaheim, CA, USA, April 28, 2012. SIAM 2012 [contents] - 2011
- [c24]Emmanuel Müller, Ira Assent, Stephan Günnemann, Patrick Gerwert, Matthias Hannen, Timm Jansen, Thomas Seidl:
A Framework for Evaluation and Exploration of Clustering Algorithms in Subspaces of High Dimensional Databases. BTW 2011: 347-366 - [c23]Emmanuel Müller, Ira Assent, Stephan Günnemann, Thomas Seidl:
Scalable density-based subspace clustering. CIKM 2011: 1077-1086 - [c22]Stephan Günnemann, Ines Färber, Emmanuel Müller, Ira Assent, Thomas Seidl:
External evaluation measures for subspace clustering. CIKM 2011: 1363-1372 - [c21]Emmanuel Müller, Matthias Schiffer, Thomas Seidl:
Statistical selection of relevant subspace projections for outlier ranking. ICDE 2011: 434-445 - [c20]Stephan Günnemann, Emmanuel Müller, Sebastian Raubach, Thomas Seidl:
Flexible Fault Tolerant Subspace Clustering for Data with Missing Values. ICDM 2011: 231-240 - [c19]Andranik Khachatryan, Emmanuel Müller, Klemens Böhm, Jonida Kopper:
Efficient Selectivity Estimation by Histogram Construction Based on Subspace Clustering. SSDBM 2011: 351-368 - [e1]Emmanuel Müller, Stephan Günnemann, Ira Assent, Thomas Seidl:
Proceedings of the 2nd MultiClust Workshop: Discovering, Summarizing and Using Multiple Clusterings, Athens, Greece, September 5, 2011, in conjunction with ECML/PKDD 2011. CEUR Workshop Proceedings 772, CEUR-WS.org 2011 [contents] - 2010
- [b1]Emmanuel Alexander Müller:
Efficient knowledge discovery in subspaces of high dimensional databases. RWTH Aachen University, 2010, pp. 1-270 - [c18]Emmanuel Müller, Matthias Schiffer, Thomas Seidl:
Adaptive outlierness for subspace outlier ranking. CIKM 2010: 1629-1632 - [c17]Emmanuel Müller, Philipp Kranen, Michael Nett, Felix Reidl, Thomas Seidl:
Air-Indexing on Error Prone Communication Channels. DASFAA (1) 2010: 505-519 - [c16]Emmanuel Müller, Stephan Günnemann, Ines Färber, Thomas Seidl:
Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data. ICDM 2010: 1220 - [c15]Emmanuel Müller, Matthias Schiffer, Patrick Gerwert, Matthias Hannen, Timm Jansen, Thomas Seidl:
SOREX: Subspace Outlier Ranking Exploration Toolkit. ECML/PKDD (3) 2010: 607-610
2000 – 2009
- 2009
- [j4]Matthias Schiffer, Emmanuel Müller, Thomas Seidl:
SubRank: Ranking Local Outliers in Projections of High-Dimensional Spaces. Datenbank-Spektrum 9(29): 53-55 (2009) - [j3]Emmanuel Müller, Stephan Günnemann, Ira Assent, Thomas Seidl:
Evaluating Clustering in Subspace Projections of High Dimensional Data. Proc. VLDB Endow. 2(1): 1270-1281 (2009) - [c14]Stephan Günnemann, Emmanuel Müller, Ines Färber, Thomas Seidl:
Detection of orthogonal concepts in subspaces of high dimensional data. CIKM 2009: 1317-1326 - [c13]Emmanuel Müller, Ira Assent, Stephan Günnemann, Ralph Krieger, Thomas Seidl:
Relevant Subspace Clustering: Mining the Most Interesting Non-redundant Concepts in High Dimensional Data. ICDM 2009: 377-386 - [c12]Marwan Hassani, Emmanuel Müller, Thomas Seidl:
EDISKCO: energy efficient distributed in-sensor-network k-center clustering with outliers. KDD Workshop on Knowledge Discovery from Sensor Data 2009: 39-48 - [c11]Emmanuel Müller, Ira Assent, Ralph Krieger, Stephan Günnemann, Thomas Seidl:
DensEst: Density Estimation for Data Mining in High Dimensional Spaces. SDM 2009: 175-186 - [c10]Emmanuel Müller, Ira Assent, Thomas Seidl:
HSM: Heterogeneous Subspace Mining in High Dimensional Data. SSDBM 2009: 497-516 - 2008
- [j2]David Ruau, Corinna Kolárik, Heinz-Theodor Mevissen, Emmanuel Müller, Ira Assent, Ralph Krieger, Thomas Seidl, Martin Hofmann-Apitius, Martin Zenke:
Public microarray repository semantic annotation with ontologies employing text mining and expression profile correlation. BMC Bioinform. 9(S-10) (2008) - [c9]Ira Assent, Ralph Krieger, Emmanuel Müller, Thomas Seidl:
EDSC: efficient density-based subspace clustering. CIKM 2008: 1093-1102 - [c8]Emmanuel Müller, Ira Assent, Uwe Steinhausen, Thomas Seidl:
OutRank: ranking outliers in high dimensional data. ICDE Workshops 2008: 600-603 - [c7]Ira Assent, Ralph Krieger, Emmanuel Müller, Thomas Seidl:
INSCY: Indexing Subspace Clusters with In-Process-Removal of Redundancy. ICDM 2008: 719-724 - [c6]Emmanuel Müller, Ira Assent, Ralph Krieger, Timm Jansen, Thomas Seidl:
Morpheus: interactive exploration of subspace clustering. KDD 2008: 1089-1092 - [c5]Philipp Kranen, David Kensche, Saim Kim, Nadine Zimmermann, Emmanuel Müller, Christoph Quix, Xiang Li, Thomas Gries, Thomas Seidl, Matthias Jarke, Steffen Leonhardt:
Mobile Mining and Information Management in HealthNet Scenarios. MDM 2008: 215-216 - [c4]Ira Assent, Emmanuel Müller, Ralph Krieger, Timm Jansen, Thomas Seidl:
Pleiades: Subspace Clustering and Evaluation. ECML/PKDD (2) 2008: 666-671 - [i2]Thomas Seidl, Emmanuel Müller, Ira Assent, Uwe Steinhausen:
Outlier detection and ranking based on subspace clustering. Uncertainty Management in Information Systems 2008 - 2007
- [j1]Ira Assent, Ralph Krieger, Emmanuel Müller, Thomas Seidl:
VISA: visual subspace clustering analysis. SIGKDD Explor. 9(2): 5-12 (2007) - [c3]Emmanuel Müller:
Subspace Clustering für die Analyse von CGH Daten. BTW Studierendenprogramm 2007: 31-33 - [c2]Ira Assent, Ralph Krieger, Emmanuel Müller, Thomas Seidl:
DUSC: Dimensionality Unbiased Subspace Clustering. ICDM 2007: 409-414 - [i1]Ira Assent, Ralph Krieger, Emmanuel Müller, Thomas Seidl:
Subspace outlier mining in large multimedia databases. Parallel Universes and Local Patterns 2007 - 2006
- [c1]Maximilian Möllers, Emmanuel Müller, Daniel Neider, Leszek Seweryn:
MediSign - Secure Pharmaceutic Distribution. Informatiktage 2006: 113-115
Coauthor Index
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Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-07 21:32 CET by the dblp team
all metadata released as open data under CC0 1.0 license
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since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
