11 Publikationen
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2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982084Personalized Online Learning of Whole-Body Motion Classes using Multiple Inertial Measurement UnitsPUB | DOI
Losing, Viktor, Personalized Online Learning of Whole-Body Motion Classes using Multiple Inertial Measurement Units. 2019 International Conference on Robotics and Automation (ICRA) (). , 2019 -
2019 | Bielefelder E-Dissertation | PUB-ID: 2936581Memory Models for Incremental Learning ArchitecturesPUB | PDF | DOI
Losing, Viktor, Memory Models for Incremental Learning Architectures. (). Bielefeld, 2019 -
2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982088Enhancing Very Fast Decision Trees with Local Split-Time PredictionsPUB | DOI
Losing, Viktor, Enhancing Very Fast Decision Trees with Local Split-Time Predictions. 2018 IEEE International Conference on Data Mining (ICDM) (). , 2018 -
2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2917201Tackling heterogeneous concept drift with the Self-Adjusting Memory (SAM)PUB | DOI | WoS
Losing, Viktor, Tackling heterogeneous concept drift with the Self-Adjusting Memory (SAM). KNOWLEDGE AND INFORMATION SYSTEMS 54 (1). , 2018 -
2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2914730Incremental on-line learning: A review and comparison of state of the art algorithmsPUB | PDF | DOI | WoS
Losing, Viktor, Incremental on-line learning: A review and comparison of state of the art algorithms. Neurocomputing 275 (). , 2018 -
2017 | Konferenzbeitrag | PUB-ID: 2914734Self-Adjusting Memory: How to Deal with Diverse Drift TypesPUB | PDF | DOI
Losing, Viktor, Self-Adjusting Memory: How to Deal with Diverse Drift Types. (). , 2017 -
2017 | Konferenzbeitrag | PUB-ID: 2914732Personalized Maneuver Prediction at IntersectionsPUB | PDF
Losing, Viktor, Personalized Maneuver Prediction at Intersections. (). , 2017 -
2016 | Konferenzbeitrag | PUB-ID: 2907624Choosing the Best Algorithm for an Incremental On-line Learning TaskPUB | PDF
Losing, Viktor, Choosing the Best Algorithm for an Incremental On-line Learning Task. (). , 2016 -
2016 | Konferenzbeitrag | PUB-ID: 2908455Dedicated Memory Models for Continual Learning in the Presence of Concept DriftPUB | PDF
Losing, Viktor, Dedicated Memory Models for Continual Learning in the Presence of Concept Drift. (). , 2016 -
2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2907622KNN Classifier with Self Adjusting Memory for Heterogeneous Concept DriftPUB | PDF | DOI
Losing, Viktor, KNN Classifier with Self Adjusting Memory for Heterogeneous Concept Drift. 2016 IEEE 16th International Conference on Data Mining (ICDM) (). Piscataway, NJ, 2016 -
2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2776021Interactive Online Learning for Obstacle Classification on a Mobile RobotPUB | PDF | DOI
Losing, Viktor, Interactive Online Learning for Obstacle Classification on a Mobile Robot. (). , 2015