Viktor Losing — accepted AI-conference papers

2020

Personalized Online Learning with Pseudo-Ground Truth

Viktor Losing, Martina Hasenjäger, Taizo Yoshikawa

IROS 2020poster

Personalized online machine learning allows a very accurate modelling of individual behavior and demands. In particular, a system that dynamically adapts during runtime can initiate a continuous collaboration with its user where both alternately adjust to each other to maximize the system's utility.…

Cited by 1 Source ↗Scholar ↗

2019

Personalized Online Learning of Whole-Body Motion Classes using Multiple Inertial Measurement Units

Viktor Losing, Taizo Yoshikawa, Martina Hasenjaeger, Barbara Hammer, Heiko Wersing

ICRA 2019poster

Online action classification is an important field of research, enabling the particularly interesting application scenario of controlling wearable devices which actively support the user's motions. The majority of machine learning applications of real-world systems are based on pre-trained average-u…

Cited by 8 Source ↗Scholar ↗