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ORCIDGeorg Krempl
Person information
- affiliation: Otto von Guericke University Magdeburg, Faculty of Computer Science, Germany
- affiliation: University of Graz, Department of Statistics and Operations Research, Austria
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2020 – today
- 2023
[c22]Mirko Bunse, Georg Krempl, Alaa Tharwat, Amal Saadallah:
Tutorial: Interactive Adaptive Learning. IAL@PKDD/ECML 2023: 1-8- [e8]Mirko Bunse, Barbara Hammer, Georg Krempl, Vincent Lemaire, Alaa Tharwat, Amal Saadallah:
Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2023), Torino, Italy, September 22nd, 2023. CEUR Workshop Proceedings 3470, CEUR-WS.org 2023 [contents] - 2022
- [j9]Tuan Pham, Daniel Kottke, Georg Krempl, Bernhard Sick:
Stream-based active learning for sliding windows under the influence of verification latency. Mach. Learn. 111(6): 2011-2036 (2022) - [c21]Daniel Kottke
, Christoph Sandrock, Georg Krempl, Bernhard Sick:
A Stopping Criterion for Transductive Active Learning. ECML/PKDD (4) 2022: 468-484 - [e7]Georg Krempl, Vincent Lemaire, Daniel Kottke, Andreas Holzinger, Barbara Hammer:
Proceedings of the Workshop on Interactive Adaptive Learning (IAL 2021) co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2021), Bilbao, Spain, September 13, 2021. CEUR Workshop Proceedings 3079, CEUR-WS.org 2022 [contents] - [e6]Daniel Kottke, Georg Krempl, Andreas Holzinger, Barbara Hammer:
Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2022), Grenoble, France, September 23, 2022. CEUR Workshop Proceedings 3259, CEUR-WS.org 2022 [contents] - 2021
- [j8]Daniel Kottke, Marek Herde, Christoph Sandrock, Denis Huseljic, Georg Krempl, Bernhard Sick:
Toward optimal probabilistic active learning using a Bayesian approach. Mach. Learn. 110(6): 1199-1231 (2021) - [j7]Thomas T. Kok, Georg Krempl, Hugo G. Schnack:
Implementation of and experimental software for active selection of classification features. Softw. Impacts 9: 100103 (2021) - [c20]Georg Krempl, Daniel Kottke, Tuan Pham:
Statistical Analysis of Pairwise Connectivity. DS 2021: 138-148 - [c19]Thomas T. Kok, Rachel M. Brouwer, René C. W. Mandl, Hugo G. Schnack, Georg Krempl:
Active Selection of Classification Features. IDA 2021: 184-195 - [i6]Thomas T. Kok, Rachel M. Brouwer, René C. W. Mandl, Hugo G. Schnack, Georg Krempl:
Active Selection of Classification Features. CoRR abs/2102.13636 (2021) - [i5]Daniel Kottke, Georg Krempl, Marianne Stecklina, Cornelius Styp von Rekowski, Tim Sabsch, Tuan Pham Minh, Matthias Deliano, Myra Spiliopoulou, Bernhard Sick:
Probabilistic Active Learning for Active Class Selection. CoRR abs/2108.03891 (2021) - [i4]Georg Krempl, Daniel Kottke, Tuan Pham Minh:
ACE: A Novel Approach for the Statistical Analysis of Pairwise Connectivity. CoRR abs/2108.04289 (2021) - 2020
- [c18]Koen Niemeijer, Remco Feskens, Georg Krempl, Jesse Koops, Matthieu J. S. Brinkhuis:
Constructing and predicting school advice for academic achievement: a comparison of item response theory and machine learning techniques. LAK 2020: 462-471 - [e5]Michael R. Berthold, Ad Feelders, Georg Krempl:
Advances in Intelligent Data Analysis XVIII - 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27-29, 2020, Proceedings. Lecture Notes in Computer Science 12080, Springer 2020, ISBN 978-3-030-44583-6 [contents] - [e4]Daniel Kottke, Georg Krempl, Vincent Lemaire, Andreas Holzinger, Adrian Calma:
Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2020), Ghent, Belgium, September 14th, 2020. CEUR Workshop Proceedings 2660, CEUR-WS.org 2020 [contents] - [i3]Daniel Kottke, Marek Herde, Christoph Sandrock, Denis Huseljic, Georg Krempl, Bernhard Sick:
Toward Optimal Probabilistic Active Learning Using a Bayesian Approach. CoRR abs/2006.01732 (2020) - [i2]Georg Krempl, Vera Hofer, Geoffrey I. Webb, Eyke Hüllermeier:
Beyond Adaptation: Understanding Distributional Changes (Dagstuhl Seminar 20372). Dagstuhl Reports 10(4): 1-36 (2020)
2010 – 2019
- 2019
- [j6]Georg Krempl, Dominik Lang, Vera Hofer:
Temporal density extrapolation using a dynamic basis approach. Data Min. Knowl. Discov. 33(5): 1323-1356 (2019) - [i1]Georg Krempl, Dominik Lang, Vera Hofer:
Temporal Density Extrapolation using a Dynamic Basis Approach. CoRR abs/1906.00912 (2019) - 2018
- [e3]Georg Krempl, Vincent Lemaire, Daniel Kottke, Adrian Calma, Andreas Holzinger, Robi Polikar, Bernhard Sick:
Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning (ECML 2018) and Principles and Practice of Knowledge Discovery in Databases (PKDD 2018), Dublin, Ireland, September 10th, 2018. CEUR Workshop Proceedings 2192, CEUR-WS.org 2018 [contents] - 2017
- [c17]Daniel Kottke, Adrian Calma, Denis Huseljic, Georg Krempl, Bernhard Sick:
Challenges of Reliable, Realistic and Comparable Active Learning Evaluation. IAL@PKDD/ECML 2017: 2-14 - [c16]Dominik Lang, Daniel Kottke, Georg Krempl:
Probabilistic Active Learning with Structure-Sensitive Kernels. IAL@PKDD/ECML 2017: 37-48 - [e2]Georg Krempl, Vincent Lemaire, Robi Polikar, Bernhard Sick, Daniel Kottke, Adrian Calma:
Proceedings of the Workshop and Tutorial on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2017), Skopje, Macedonia, September 18, 2017. CEUR Workshop Proceedings 1924, CEUR-WS.org 2017 [contents] - 2016
- [c15]Daniel Kottke, Georg Krempl, Dominik Lang, Johannes Teschner, Myra Spiliopoulou:
Multi-Class Probabilistic Active Learning. ECAI 2016: 586-594 - [c14]Dominik Lang, Daniel Kottke, Georg Krempl, Myra Spiliopoulou:
Investigating Exploratory Capabilities of Uncertainty Sampling using SVMs in Active Learning. AL@iKNOW 2016: 25-34 - [c13]Benjamin Bergner, Georg Krempl:
Active Subtopic Detection in Multitopic Data. AL@iKNOW 2016: 35-44 - [e1]Georg Krempl, Vincent Lemaire, Edwin Lughofer, Daniel Kottke:
Proceedings of the Workshop on Active Learning: Applications, Foundations and Emerging Trends co-located with International Conference on Knowledge Technologies and Data-driven Business (i-KNOW 2016), Graz, Austria, October 18, 2016. CEUR Workshop Proceedings 1707, CEUR-WS.org 2016 [contents] - 2015
- [j5]Zaigham Faraz Siddiqui, Georg Krempl, Myra Spiliopoulou, José M. Peña, Nuria Paul, Fernando Maestú:
Predicting the post-treatment recovery of patients suffering from traumatic brain injury (TBI). Brain Informatics 2(1): 33-44 (2015) - [j4]Georg Krempl, Daniel Kottke, Vincent Lemaire:
Optimised probabilistic active learning (OPAL) - For fast, non-myopic, cost-sensitive active classification. Mach. Learn. 100(2-3): 449-476 (2015) - [c12]Georg Krempl, Tuan Cuong Ha, Myra Spiliopoulou:
Clustering-Based Optimised Probabilistic Active Learning (COPAL). Discovery Science 2015: 101-115 - [c11]Daniel Kottke, Georg Krempl, Myra Spiliopoulou:
Probabilistic Active Learning in Datastreams. IDA 2015: 145-157 - [c10]Christian Beyer, Georg Krempl, Vincent Lemaire:
How to select information that matters: a comparative study on active learning strategies for classification. I-KNOW 2015: 2:1-2:8 - [c9]Georg Krempl:
Temporal Density Extrapolation. AALTD@PKDD/ECML 2015 - 2014
- [j3]Georg Krempl, Indre Zliobaite, Dariusz Brzezinski, Eyke Hüllermeier, Mark Last, Vincent Lemaire, Tino Noack, Ammar Shaker, Sonja Sievi, Myra Spiliopoulou, Jerzy Stefanowski:
Open challenges for data stream mining research. SIGKDD Explor. 16(1): 1-10 (2014) - [c8]Zaigham Faraz Siddiqui, Georg Krempl, Myra Spiliopoulou, José M. Peña, Nuria Paul, Fernando Maestú:
Are Some Brain Injury Patients Improving More Than Others? Brain Informatics and Health 2014: 376-387 - [c7]Georg Krempl, Daniel Kottke, Myra Spiliopoulou:
Probabilistic Active Learning: Towards Combining Versatility, Optimality and Efficiency. Discovery Science 2014: 168-179 - [c6]Georg Krempl, Daniel Kottke, Myra Spiliopoulou:
Probabilistic Active Learning: A Short Proposition. ECAI 2014: 1049-1050 - 2013
- [j2]Vera Hofer, Georg Krempl:
Drift mining in data: A framework for addressing drift in classification. Comput. Stat. Data Anal. 57(1): 377-391 (2013) - [c5]Pawel Matuszyk, Georg Krempl, Myra Spiliopoulou:
Correcting the Usage of the Hoeffding Inequality in Stream Mining. IDA 2013: 298-309 - 2012
- [j1]Vera Hofer, Georg Krempl:
A hierarchical tree layout algorithm with an application to corporate management in a change process. Expert Syst. Appl. 39(15): 12123-12130 (2012) - 2011
- [c4]Georg Krempl, Vera Hofer:
Classification in Presence of Drift and Latency. ICDM Workshops 2011: 596-603 - [c3]Georg Krempl:
The Algorithm APT to Classify in Concurrence of Latency and Drift. IDA 2011: 222-233 - [c2]Georg Krempl, Vera Hofer:
Drift Models and Classification in Presence of Latency and Drift. LWA 2011: 65-72 - [c1]Georg Krempl, Zaigham Faraz Siddiqui, Myra Spiliopoulou:
Online Clustering of High-Dimensional Trajectories under Concept Drift. ECML/PKDD (2) 2011: 261-276
2000 – 2009
- 2009
- [p1]Georg Krempl, Vera Hofer:
Partitioner Trees for Classification: A New Ensemble Method. Applications of Supervised and Unsupervised Ensemble Methods 2009: 93-112
Coauthor Index
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last updated on 2023-09-28 02:47 CEST by the dblp team
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