3 accepted papers
Offline meta-reinforcement learning (meta-RL) aims to train agents that can generalize to unseen tasks using pre-collected data from related tasks. Recent approaches leverage the scalability of transformer architectures to model behavior sequences and support task adaptation using target task demons…
AI-systems that model and interact with their users can up-date their models over time to reflect new information and changes in the environment. Although these updates may improve the overall performance of the AI-system, they may actually hurt the performance with respect to individual users. Prio…
Novel wearable sensor modalities, such as bio-impedance (Bio-Z), are being introduced and often provide various advantages over current state-of-the-art in terms of accuracy, sensing coverage, or convenience of wear. The principal challenge, however, lies in the ability to interpret the sensor readi…