Viktor Losing
Viktor Losing
CrowdStrike, Paris
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Incremental on-line learning: A review and comparison of state of the art algorithms
V Losing, B Hammer, H Wersing
Neurocomputing 275, 1261-1274, 2018
KNN Classifier with Self Adjusting Memory for Heterogeneous Concept Drift
V Losing, B Hammer, H Wersing
2016 IEEE 16th International Conference on Data Mining (ICDM), 291--300, 2016
Interactive online learning for obstacle classification on a mobile robot
V Losing, B Hammer, H Wersing
2015 international joint conference on neural networks (ijcnn), 1-8, 2015
Tackling heterogeneous concept drift with the Self-Adjusting Memory (SAM)
V Losing, B Hammer, H Wersing
Knowledge and Information Systems 54, 171-201, 2018
Self-adjusting memory: How to deal with diverse drift types
V Losing, B Hammer, H Wersing
International Joint Conference on Artificial Intelligence, 2017
Choosing the Best Algorithm for an Incremental On-line Learning Task
V Losing, B Hammer, H Wersing
European Symposium on Artificial Neural Networks (ESANN), 369-374, 2016
Guiding visual search tasks using gaze-contingent auditory feedback
V Losing, L Rottkamp, M Zeunert, T Pfeiffer
Proceedings of the 2014 ACM International Joint Conference on Pervasive and …, 2014
A multi-modal gait database of natural everyday-walk in an urban environment
V Losing, M Hasenjäger
Scientific data 9 (1), 473, 2022
Personalized maneuver prediction at intersections
V Losing, B Hammer, H Wersing
2017 ieee 20th international conference on intelligent transportation …, 2017
Learning fast and slow: A unified batch/stream framework
J Montiel, A Bifet, V Losing, J Read, T Abdessalem
2018 IEEE International Conference on Big Data (Big Data), 1065-1072, 2018
Extraction of common-sense relations from procedural task instructions using BERT
V Losing, L Fischer, J Deigmöller
Proceedings of the 11th Global Wordnet Conference, 81-90, 2021
Machine learning for human movement understanding
T Yoshikawa, V Losing, E Demircan
Advanced Robotics 34 (13), 828-844, 2020
Enhancing very fast decision trees with local split-time predictions
V Losing, H Wersing, B Hammer
2018 IEEE international conference on data mining (ICDM), 287-296, 2018
Randomizing the self-adjusting memory for enhanced handling of concept drift
V Losing, B Hammer, H Wersing, A Bifet
2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020
Personalized online learning of whole-body motion classes using multiple inertial measurement units
V Losing, T Yoshikawa, M Hasenjaeger, B Hammer, H Wersing
2019 International Conference on Robotics and Automation (ICRA), 9530-9536, 2019
Situational Question Answering using Memory Nets.
J Deigmoeller, P Smirnov, V Losing, C Wang, J Takeuchi, J Eggert
KDIR, 169-176, 2022
Extraction of common physical properties of everyday objects from structured sources
V Losing, J Eggert
Proceedings of the 2022 6th International Conference on Natural Language …, 2022
Dedicated Memory Models for Continual Learning in the Presence of Concept Drift
V Losing, B Hammer, H Wersing
Continual Learning Workshop of the Thirtieth Annual Conference on Neural …, 2016
Personalized Online Learning with Pseudo-Ground Truth
V Losing, M Hasenjäger, T Yoshikawa
International Conference on Intelligent Robots and Systems, 2020
Memory Models for Incremental Learning Architectures
V Losing
Bielefeld University, 2019
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