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ORCIDKatharina Morik
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- affiliation: Technical University of Dortmund, Germany
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2020 – today
- 2024
[j54]Raphael Fischer, Thomas Liebig, Katharina Morik:
Towards more sustainable and trustworthy reporting in machine learning. Data Min. Knowl. Discov. 38(4): 1909-1928 (2024)- 2023
- [j53]Sebastian Buschjäger
, Katharina Morik:
Joint leaf-refinement and ensemble pruning through L1 regularization. Data Min. Knowl. Discov. 37(3): 1230-1261 (2023) - [i29]Raphael Fischer, Matthias Jakobs, Katharina Morik:
Energy Efficiency Considerations for Popular AI Benchmarks. CoRR abs/2304.08359 (2023) - [i28]Simon Koschel, Sebastian Buschjäger, Claudio Lucchese, Katharina Morik:
Fast Inference of Tree Ensembles on ARM Devices. CoRR abs/2305.08579 (2023) - 2022
- [j52]Amal Saadallah, Felix Finkeldey, Jens Buß, Katharina Morik, Petra Wiederkehr, Wolfgang Rhode:
Simulation and sensor data fusion for machine learning application. Adv. Eng. Informatics 52: 101600 (2022) - [j51]Katharina Morik, Helena Kotthaus, Raphael Fischer, Sascha Mücke, Matthias Jakobs, Nico Piatkowski, Andreas Pauly, Lukas Heppe, Danny Heinrich:
Yes we care!-Certification for machine learning methods through the care label framework. Frontiers Artif. Intell. 5 (2022) - [j50]Sebastian Buschjäger, Philipp-Jan Honysz, Katharina Morik:
Randomized outlier detection with trees. Int. J. Data Sci. Anal. 13(2): 91-104 (2022) - [j49]Amal Saadallah, Matthias Jakobs, Katharina Morik:
Explainable online ensemble of deep neural network pruning for time series forecasting. Mach. Learn. 111(9): 3459-3487 (2022) - [j48]Mikail Yayla, Sebastian Buschjäger, Aniket Gupta, Jian-Jia Chen, Jörg Henkel, Katharina Morik, Kuan-Hsun Chen, Hussam Amrouch:
FeFET-Based Binarized Neural Networks Under Temperature-Dependent Bit Errors. IEEE Trans. Computers 71(7): 1681-1695 (2022) - [j47]Mikail Yayla, Simon Thomann, Sebastian Buschjäger, Katharina Morik, Jian-Jia Chen, Hussam Amrouch:
Reliable Binarized Neural Networks on Unreliable Beyond Von-Neumann Architecture. IEEE Trans. Circuits Syst. I Regul. Pap. 69(6): 2516-2528 (2022) - [j46]Kuan-Hsun Chen, Chiahui Su, Christian Hakert, Sebastian Buschjäger, Chao-Lin Lee, Jenq-Kuen Lee, Katharina Morik, Jian-Jia Chen:
Efficient Realization of Decision Trees for Real-Time Inference. ACM Trans. Embed. Comput. Syst. 21(6): 68:1-68:26 (2022) - [c114]Sebastian Buschjäger, Sibylle Hess, Katharina Morik:
Shrub Ensembles for Online Classification. AAAI 2022: 6123-6131 - [c113]Amal Saadallah, Hanna Mykula, Katharina Morik:
Online Adaptive Multivariate Time Series Forecasting. ECML/PKDD (6) 2022: 19-35 - [c112]Raphael Fischer, Matthias Jakobs, Sascha Mücke, Katharina Morik:
A Unified Framework for Assessing Energy Efficiency of Machine Learning. PKDD/ECML Workshops (1) 2022: 39-54 - [c111]Martin Senz, Mirko Bunse, Katharina Morik:
Certifiable Active Class Selection in Multi-Class Classification. IAL@PKDD/ECML 2022: 68-76 - [p18]Katharina Morik, Jian-Jia Chen:
Introduction. Mach. Learn. under Resour. Constraints Vol. 1 (1) 2022: 1-13 - [p17]Katharina Morik, Jörg Rahnenführer, Christian Wietfeld:
Editorial. Mach. Learn. under Resour. Constraints Vol. 3 (3) 2022: 1-2 - [p16]Wolfgang Rhode, Katharina Morik:
Introduction. Mach. Learn. under Resour. Constraints Vol. 2 (2) 2022: 1-29 - [p15]Katharina Morik, Mirko Bunse:
Key Concepts in Machine Learning and Data Analysis. Mach. Learn. under Resour. Constraints Vol. 2 (2) 2022: 51-75 - [p14]Sebastian Buschjäger, Katharina Morik:
Summary Extraction from Streams. Mach. Learn. under Resour. Constraints Vol. 1 (1) 2022: 73-84 - [p13]Nico Piatkowski, Katharina Morik:
Spatio-Temporal Random Fields. Mach. Learn. under Resour. Constraints Vol. 1 (1) 2022: 100-115 - [p12]Jochen Deuse, Katharina Morik, Amal Saadallah, Jan Büscher, Thorben Panusch:
Quality Assurance in Interlinked Manufacturing Processes. Mach. Learn. under Resour. Constraints Vol. 3 (3) 2022: 114-135 - [p11]Marco Stolpe, Katharina Morik:
Label Proportion Learning. Mach. Learn. under Resour. Constraints Vol. 3 (3) 2022: 136-156 - [p10]Petra Wiederkehr, Katharina Morik, Amal Saadallah, Felix Finkeldey:
Simulation and Machine Learning. Mach. Learn. under Resour. Constraints Vol. 3 (3) 2022: 157-179 - [e14]Katharina Morik, Peter Marwedel:
Machine Learning under Resource Constraints - Volume 1: Fundamentals. De Gruyter STEM, De Gruyter 2022, ISBN 978-3-11-078593-7 [contents] - [e13]Katharina Morik, Wolfgang Rhode:
Machine Learning under Resource Constraints - Volume 2: Discovery in Physics. De Gruyter STEM, De Gruyter 2022, ISBN 978-3-11-078595-1 [contents] - [e12]Katharina Morik, Jörg Rahnenführer, Christian Wietfeld:
Machine Learning under Resource Constraints - Volume 3: Applications. De Gruyter STEM, De Gruyter 2022, ISBN 978-3-11-078597-5 [contents] - [i27]Lukas Pfahler, Katharina Morik:
Self-Supervised Pretraining of Graph Neural Network for the Retrieval of Related Mathematical Expressions in Scientific Articles. CoRR abs/2209.00446 (2022) - 2021
- [j45]Mirco Nanni, Gennady L. Andrienko, Albert-László Barabási, Chiara Boldrini, Francesco Bonchi, Ciro Cattuto, Francesca Chiaromonte, Giovanni Comandè, Marco Conti, Mark Coté, Frank Dignum, Virginia Dignum, Josep Domingo-Ferrer, Paolo Ferragina, Fosca Giannotti, Riccardo Guidotti, Dirk Helbing, Kimmo Kaski, János Kertész, Sune Lehmann, Bruno Lepri, Paul Lukowicz, Stan Matwin, David Megías Jiménez, Anna Monreale, Katharina Morik, Nuria Oliver, Andrea Passarella, Andrea Passerini, Dino Pedreschi, Alex Pentland, Fabio Pianesi, Francesca Pratesi, Salvatore Rinzivillo, Salvatore Ruggieri, Arno Siebes, Vicenç Torra, Roberto Trasarti, Jeroen van den Hoven, Alessandro Vespignani:
Give more data, awareness and control to individual citizens, and they will help COVID-19 containment. Ethics Inf. Technol. 23(S1): 1-6 (2021) - [c110]Sebastian Buschjäger, Jian-Jia Chen, Kuan-Hsun Chen, Mario Günzel, Christian Hakert, Katharina Morik, Rodion Novkin, Lukas Pfahler, Mikail Yayla:
Margin-Maximization in Binarized Neural Networks for Optimizing Bit Error Tolerance. DATE 2021: 673-678 - [c109]Amal Saadallah, Katharina Morik:
Online Ensemble Aggregation using Deep Reinforcement Learning for Time Series Forecasting. DSAA 2021: 1-8 - [c108]Amal Saadallah, Maryam Tavakol, Katharina Morik:
An Actor-Critic Ensemble Aggregation Model for Time-Series Forecasting. ICDE 2021: 2255-2260 - [c107]Amal Saadallah, Katharina Morik:
Meta-Adversarial Training of Neural Networks for Binary Classification. IJCNN 2021: 1-7 - [c106]Felix Gonsior, Sascha Mücke, Katharina Morik:
Structure Search for Normalizing Flows. LWDA 2021: 98-105 - [c105]Mirko Bunse, Katharina Morik:
Active Class Selection with Uncertain Class Proportions. IAL@PKDD/ECML 2021: 70-79 - [c104]Sebastian Buschjäger, Philipp-Jan Honysz, Lukas Pfahler, Katharina Morik:
Very Fast Streaming Submodular Function Maximization. ECML/PKDD (3) 2021: 151-166 - [c103]Mirko Bunse, Katharina Morik:
Certification of Model Robustness in Active Class Selection. ECML/PKDD (2) 2021: 266-281 - [c102]Amal Saadallah, Matthias Jakobs, Katharina Morik:
Explainable Online Deep Neural Network Selection Using Adaptive Saliency Maps for Time Series Forecasting. ECML/PKDD (1) 2021: 404-420 - [c101]Georg von der Brüggen, Nico Piatkowski, Kuan-Hsun Chen, Jian-Jia Chen, Katharina Morik, Björn B. Brandenburg:
Efficiently Approximating the Worst-Case Deadline Failure Probability Under EDF. RTSS 2021: 214-226 - [p9]Raja Chatila, Virginia Dignum, Michael Fisher, Fosca Giannotti, Katharina Morik, Stuart Russell, Karen Yeung:
Trustworthy AI. Reflections on Artificial Intelligence for Humanity 2021: 13-39 - [i26]Philipp-Jan Honysz, Sebastian Buschjäger, Katharina Morik:
GPU-Accelerated Optimizer-Aware Evaluation of Submodular Exemplar Clustering. CoRR abs/2101.08763 (2021) - [i25]Sebastian Buschjäger, Jian-Jia Chen, Kuan-Hsun Chen, Mario Günzel, Katharina Morik, Rodion Novkin, Lukas Pfahler, Mikail Yayla:
Bit Error Tolerance Metrics for Binarized Neural Networks. CoRR abs/2102.01344 (2021) - [i24]Katharina Morik, Helena Kotthaus, Lukas Heppe, Danny Heinrich, Raphael Fischer, Sascha Mücke, Andreas Pauly, Matthias Jakobs, Nico Piatkowski:
Yes We Care! - Certification for Machine Learning Methods through the Care Label Framework. CoRR abs/2105.10197 (2021) - [i23]Philipp-Jan Honysz, Alexander Schulze-Struchtrup, Sebastian Buschjäger, Katharina Morik:
Providing Meaningful Data Summarizations Using Examplar-based Clustering in Industry 4.0. CoRR abs/2105.12026 (2021) - [i22]Katharina Morik, Helena Kotthaus, Lukas Heppe, Danny Heinrich, Raphael Fischer, Andreas Pauly, Nico Piatkowski:
The Care Label Concept: A Certification Suite for Trustworthy and Resource-Aware Machine Learning. CoRR abs/2106.00512 (2021) - [i21]Lukas Pfahler, Mirko Bunse, Katharina Morik:
Noisy Labels for Weakly Supervised Gamma Hadron Classification. CoRR abs/2108.13396 (2021) - [i20]Lukas Pfahler, Katharina Morik:
Explaining Deep Learning Representations by Tracing the Training Process. CoRR abs/2109.05880 (2021) - [i19]Sebastian Buschjäger, Katharina Morik:
Improving the Accuracy-Memory Trade-Off of Random Forests Via Leaf-Refinement. CoRR abs/2110.10075 (2021) - [i18]Sebastian Buschjäger, Katharina Morik:
There is no Double-Descent in Random Forests. CoRR abs/2111.04409 (2021) - [i17]Sebastian Buschjäger, Sibylle Hess, Katharina Morik:
Shrub Ensembles for Online Classification. CoRR abs/2112.03723 (2021) - 2020
- [j44]Felix Finkeldey, Amal Saadallah, Petra Wiederkehr, Katharina Morik:
Real-time prediction of process forces in milling operations using synchronized data fusion of simulation and sensor data. Eng. Appl. Artif. Intell. 94: 103753 (2020) - [j43]Mirco Nanni, Gennady L. Andrienko, Albert-László Barabási, Chiara Boldrini, Francesco Bonchi, Ciro Cattuto, Francesca Chiaromonte, Giovanni Comandè, Marco Conti, Mark Coté, Frank Dignum, Virginia Dignum, Josep Domingo-Ferrer, Paolo Ferragina, Fosca Giannotti, Riccardo Guidotti, Dirk Helbing, Kimmo Kaski, János Kertész, Sune Lehmann, Bruno Lepri, Paul Lukowicz, Stan Matwin, David Megías, Anna Monreale, Katharina Morik, Nuria Oliver, Andrea Passarella, Andrea Passerini, Dino Pedreschi, Alex Pentland, Fabio Pianesi, Francesca Pratesi, Salvatore Rinzivillo, Salvatore Ruggieri, Arno Siebes, Vicenç Torra, Roberto Trasarti, Jeroen van den Hoven, Alessandro Vespignani:
Give more data, awareness and control to individual citizens, and they will help COVID-19 containment. Trans. Data Priv. 13(1): 61-66 (2020) - [c100]Amal Saadallah, Katharina Morik:
Active Sampling for Learning Interpretable Surrogate Machine Learning Models. DSAA 2020: 264-272 - [c99]Raphael Fischer, Nico Piatkowski, Charlotte Pelletier, Geoffrey I. Webb, François Petitjean, Katharina Morik:
No Cloud on the Horizon: Probabilistic Gap Filling in Satellite Image Series. DSAA 2020: 546-555 - [c98]Sebastian Buschjäger, Philipp-Jan Honysz, Katharina Morik:
Generalized Isolation Forest: Some Theory and More Applications Extended Abstract. DSAA 2020: 793-794 - [c97]Mirko Bunse, Dorina Weichert, Alexander Kister, Katharina Morik:
Optimal Probabilistic Classification in Active Class Selection. ICDM 2020: 942-947 - [c96]Lukas Pfahler, Katharina Morik:
Semantic Search in Millions of Equations. KDD 2020: 135-143 - [c95]Raphael Fischer, Matthias Jakobs, Sascha Mücke, Katharina Morik:
Solving Abstract Reasoning Tasks with Grammatical Evolution. LWDA 2020: 6-10 - [c94]Lukas Heppe, Michael Kamp, Linara Adilova, Danny Heinrich, Nico Piatkowski, Katharina Morik:
Resource-Constrained On-Device Learning by Dynamic Averaging. PKDD/ECML Workshops 2020: 129-144 - [c93]Sebastian Buschjäger, Lukas Pfahler, Jens Buß, Katharina Morik, Wolfgang Rhode:
On-Site Gamma-Hadron Separation with Deep Learning on FPGAs. ECML/PKDD (4) 2020: 478-493 - [e11]Alexandra Poulovassilis, David Auber, Nikos Bikakis, Panos K. Chrysanthis, George Papastefanatos, Mohamed A. Sharaf, Nikos Pelekis, Chiara Renso, Yannis Theodoridis, Karine Zeitouni, Tania Cerquitelli, Silvia Chiusano, Genoveva Vargas-Solar, Behrooz Omidvar-Tehrani, Katharina Morik, Jean-Michel Renders, Donatella Firmani, Letizia Tanca, Davide Mottin, Matteo Lissandrini, Yannis Velegrakis:
Proceedings of the Workshops of the EDBT/ICDT 2020 Joint Conference, Copenhagen, Denmark, March 30, 2020. CEUR Workshop Proceedings 2578, CEUR-WS.org 2020 [contents] - [i16]Sebastian Buschjäger, Jian-Jia Chen, Kuan-Hsun Chen, Mario Günzel, Christian Hakert, Katharina Morik, Rodion Novkin, Lukas Pfahler, Mikail Yayla:
Towards Explainable Bit Error Tolerance of Resistive RAM-Based Binarized Neural Networks. CoRR abs/2002.00909 (2020) - [i15]Mirco Nanni, Gennady L. Andrienko, Albert-László Barabási, Chiara Boldrini, Francesco Bonchi, Ciro Cattuto, Francesca Chiaromonte, Giovanni Comandè, Marco Conti, Mark Coté, Frank Dignum, Virginia Dignum, Josep Domingo-Ferrer, Fosca Giannotti, Riccardo Guidotti, Dirk Helbing, János Kertész, Sune Lehmann, Bruno Lepri, Paul Lukowicz, Anna Monreale, Katharina Morik, Nuria Oliver, Andrea Passarella, Andrea Passerini, Dino Pedreschi, Alex Pentland, Francesca Pratesi, Salvatore Rinzivillo, Salvatore Ruggieri, Arno Siebes, Roberto Trasarti, Jeroen van den Hoven, Alessandro Vespignani:
Give more data, awareness and control to individual citizens, and they will help COVID-19 containment. CoRR abs/2004.05222 (2020) - [i14]Lukas Heppe, Michael Kamp, Linara Adilova, Danny Heinrich, Nico Piatkowski, Katharina Morik:
Resource-Constrained On-Device Learning by Dynamic Averaging. CoRR abs/2009.12098 (2020) - [i13]Sebastian Buschjäger, Philipp-Jan Honysz, Katharina Morik:
Very Fast Streaming Submodular Function Maximization. CoRR abs/2010.10059 (2020) - [i12]Nikolaos Nikolaou, Ingo P. Waldmann, Angelos Tsiaras, Mario Morvan, Billy Edwards, Kai Hou Yip, Giovanna Tinetti, Subhajit Sarkar, James M. Dawson, Vadim Borisov, Gjergji Kasneci, Matej Petkovic, Tomaz Stepisnik, Tarek Al-Ubaidi, Rachel Louise Bailey, Michael Granitzer, Sahib Julka, Roman Kern, Patrick Ofner, Stefan Wagner, Lukas Heppe, Mirko Bunse, Katharina Morik:
Lessons Learned from the 1st ARIEL Machine Learning Challenge: Correcting Transiting Exoplanet Light Curves for Stellar Spots. CoRR abs/2010.15996 (2020) - [i11]Sebastian Buschjäger, Lukas Pfahler, Katharina Morik:
Generalized Negative Correlation Learning for Deep Ensembling. CoRR abs/2011.02952 (2020)
2010 – 2019
- 2019
- [c92]Sibylle Hess, Wouter Duivesteijn, Philipp Honysz, Katharina Morik:
The SpectACl of Nonconvex Clustering: A Spectral Approach to Density-Based Clustering. AAAI 2019: 3788-3795 - [c91]Mirko Bunse, Nico Piatkowski, Tim Ruhe, Katharina Morik, Wolfgang Rhode:
A Data Science Perspective on Deconvolution. GI-Jahrestagung 2019: 279-280 - [c90]Sebastian Buschjäger, Thomas Liebig, Katharina Morik:
Gaussian Model Trees for Traffic Imputation. ICPRAM 2019: 243-254 - [c89]Amal Saadallah, Nico Piatkowski, Felix Finkeldey, Petra Wiederkehr, Katharina Morik:
Learning Ensembles in the Presence of Imbalanced Classes. ICPRAM 2019: 866-873 - [c88]Mirko Bunse, Katharina Morik:
What Can We Expect from Active Class Selection? LWDA 2019: 79-83 - [c87]Raphael Fischer, Nico Piatkowski, Katharina Morik:
Parameter Sharing for Spatio-Temporal Process Models. LWDA 2019: 89-93 - [c86]Felix Gonsior, Nico Piatkowski, Katharina Morik:
Another View on Optimization as Probabilistic Inference. LWDA 2019: 106-110 - [c85]Sascha Mücke, Nico Piatkowski, Katharina Morik:
Learning Bit by Bit: Extracting the Essence of Machine Learning. LWDA 2019: 144-155 - [c84]Maryam Tavakol, Sebastian Mair, Katharina Morik:
HyperUCB: Hyperparameter Optimization Using Contextual Bandits. PKDD/ECML Workshops (1) 2019: 44-50 - [c83]Sascha Mücke, Nico Piatkowski, Katharina Morik:
Hardware Acceleration of Machine Learning Beyond Linear Algebra. PKDD/ECML Workshops (1) 2019: 342-347 - [c82]Amal Saadallah, Florian Priebe, Katharina Morik:
A Drift-Based Dynamic Ensemble Members Selection Using Clustering for Time Series Forecasting. ECML/PKDD (1) 2019: 678-694 - [c81]Lukas Pfahler, Jonathan Schill, Katharina Morik:
The Search for Equations - Learning to Identify Similarities Between Mathematical Expressions. ECML/PKDD (3) 2019: 704-718 - [i10]Sibylle Hess, Katharina Morik, Nico Piatkowski:
The PRIMPing Routine - Tiling through Proximal Alternating Linearized Minimization. CoRR abs/1906.09722 (2019) - [i9]Sibylle Hess, Katharina Morik:
C-SALT: Mining Class-Specific ALTerations in Boolean Matrix Factorization. CoRR abs/1906.09907 (2019) - [i8]Sibylle Hess, Wouter Duivesteijn, Philipp Honysz, Katharina Morik:
The SpectACl of Nonconvex Clustering: A Spectral Approach to Density-Based Clustering. CoRR abs/1907.00680 (2019) - [i7]Sibylle Hess, Nico Piatkowski, Katharina Morik:
The Trustworthy Pal: Controlling the False Discovery Rate in Boolean Matrix Factorization. CoRR abs/1907.00697 (2019) - 2018
- [j42]Katharina Morik, Christian Bockermann, Sebastian Buschjäger:
Big Data Science. Künstliche Intell. 32(1): 27-36 (2018) - [j41]Sebastian Buschjäger, Katharina Morik:
Decision Tree and Random Forest Implementations for Fast Filtering of Sensor Data. IEEE Trans. Circuits Syst. I Regul. Pap. 65-I(1): 209-222 (2018) - [c80]Lukas Pfahler, Frederik Elwert, Samira Tabti, Katharina Morik, Volker Krech:
What do you do with 5 million posts? Versuche zum distant reading religiöser Online-Foren. DHd 2018 - [c79]Mirko Bunse, Nico Piatkowski, Katharina Morik, Tim Ruhe, Wolfgang Rhode:
Unification of Deconvolution Algorithms for Cherenkov Astronomy. DSAA 2018: 21-30 - [c78]Georg von der Brüggen, Nico Piatkowski, Kuan-Hsun Chen, Jian-Jia Chen, Katharina Morik:
Efficiently Approximating the Probability of Deadline Misses in Real-Time Systems. ECRTS 2018: 6:1-6:22 - [c77]Sebastian Buschjäger, Kuan-Hsun Chen, Jian-Jia Chen, Katharina Morik:
Realization of Random Forest for Real-Time Evaluation through Tree Framing. ICDM 2018: 19-28 - [c76]Mirko Bunse, Nico Piatkowski, Katharina Morik:
Towards a Unifying View on Deconvolution in Cherenkov Astronomy. LWDA 2018: 73-77 - [c75]Erich Schubert, Sibylle Hess, Katharina Morik:
The Relationship of DBSCAN to Matrix Factorization and Spectral Clustering. LWDA 2018: 330-334 - [c74]Lukas Pfahler, Katharina Morik:
Nyström-SGD: Fast Learning of Kernel-Classifiers with Conditioned Stochastic Gradient Descent. ECML/PKDD (2) 2018: 209-224 - [c73]Sibylle Hess, Nico Piatkowski, Katharina Morik:
The Trustworthy Pal: Controlling the False Discovery Rate in Boolean Matrix Factorization. SDM 2018: 405-413 - [c72]Nico Piatkowski, Katharina Morik:
Fast Stochastic Quadrature for Approximate Maximum-Likelihood Estimation. UAI 2018: 715-724 - 2017
- [j40]Sibylle Hess, Katharina Morik, Nico Piatkowski:
The PRIMPING routine - Tiling through proximal alternating linearized minimization. Data Min. Knowl. Discov. 31(4): 1090-1131 (2017) - [j39]Gennady L. Andrienko, Dimitrios Gunopulos, Yannis E. Ioannidis, Vana Kalogeraki, Ioannis Katakis, Katharina Morik, Olivier Verscheure:
Mining Urban Data (Part C). Inf. Syst. 64: 219-220 (2017) - [j38]Thomas Liebig, Nico Piatkowski, Christian Bockermann, Katharina Morik:
Dynamic route planning with real-time traffic predictions. Inf. Syst. 64: 258-265 (2017) - [c71]Frederik Elwert, Samira Tabti, Volkhard Krech, Katharina Morik, Lukas Pfahler:
relNet - Modellierung von Themen und Strukturen religiöser Online-Kommunikation. DHd 2017 - [c70]Lukas Pfahler, Katharina Morik, Frederik Elwert, Samira Tabti, Volkhard Krech:
Learning Low-Rank Document Embeddings with Weighted Nuclear Norm Regularization. DSAA 2017: 21-29 - [c69]Sebastian Buschjäger, Katharina Morik, Maik Schmidt:
Summary Extraction on Data Streams in Embedded Systems. IOTSTREAMING@PKDD/ECML 2017 - [c68]Sibylle Hess, Katharina Morik:
C-SALT: Mining Class-Specific ALTerations in Boolean Matrix Factorization. ECML/PKDD (1) 2017: 547-563 - [r2]Katharina Morik:
Medicine: Applications of Machine Learning. Encyclopedia of Machine Learning and Data Mining 2017: 809-817 - 2016
- [j37]Mario Wiegand, Marco Stolpe, Jochen Deuse, Katharina Morik:
Prädiktive Prozessüberwachung auf Basis verteilt erfasster Sensordaten. Autom. 64(7): 521-533 (2016) - [j36]Nico Piatkowski, Sangkyun Lee, Katharina Morik:
Integer undirected graphical models for resource-constrained systems. Neurocomputing 173: 9-23 (2016) - [j35]Gennady L. Andrienko, Dimitrios Gunopulos, Yannis E. Ioannidis, Vana Kalogeraki, Ioannis Katakis, Katharina Morik, Olivier Verscheure:
Mining Urban Data (Part B). Inf. Syst. 57: 75-76 (2016) - [j34]Christian Pölitz, Wouter Duivesteijn, Katharina Morik:
Interpretable domain adaptation via optimization over the Stiefel manifold. Mach. Learn. 104(2-3): 315-336 (2016) - [c67]Nico Piatkowski, Katharina Morik:
Stochastic Discrete Clenshaw-Curtis Quadrature. ICML 2016: 3000-3009 - [c66]Nikolaos Panagiotou, Nikolas Zygouras, Ioannis Katakis, Dimitrios Gunopulos, Nikos Zacheilas, Ioannis Boutsis, Vana Kalogeraki, Stephen Lynch, Brendan O'Brien, Dermot Kinane, Jakub Marecek, Jia Yuan Yu, Rudi Verago, Elizabeth Daly, Nico Piatkowski, Thomas Liebig, Christian Bockermann, Katharina Morik, François Schnitzler, Matthias Weidlich, Avigdor Gal, Shie Mannor, Hendrik Stange, Werner Halft, Gennady L. Andrienko:
INSIGHT: Dynamic Traffic Management Using Heterogeneous Urban Data. ECML/PKDD (3) 2016: 22-26 - [c65]Hendrik Blom, Katharina Morik:
Resource-Aware Steel Production Through Data Mining. ECML/PKDD (3) 2016: 263-266 - [p8]Marco Stolpe, Hendrik Blom, Katharina Morik:
Sustainable Industrial Processes by Embedded Real-Time Quality Prediction. Computational Sustainability 2016: 201-243 - [e10]Jörg Lässig, Kristian Kersting, Katharina Morik:
Computational Sustainability. Studies in Computational Intelligence 645, Springer 2016, ISBN 978-3-319-31856-1 [contents] - [i6]Elena Erdmann, Karin Boczek, Lars Koppers, Gerret von Nordheim, Christian Pölitz, Alejandro Molina, Katharina Morik, Henrik Müller, Jörg Rahnenführer, Kristian Kersting:
Machine Learning meets Data-Driven Journalism: Boosting International Understanding and Transparency in News Coverage. CoRR abs/1606.05110 (2016) - 2015
- [c64]Christian Pölitz, Katharina Morik:
Big Data und Data Mining in den Digital Humanities. DHd 2015 - [c63]