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Hyperdimensional (HD) computing is a novel approach to machine learning inspired by neuroscience, which uses vectors in a hyper-dimensional space to represent data and models. This approach has gained significant interest in recent years with applications ...
Interactive simulations encourage students to practice skills essential to understanding and learning sciences. Alas, inquiry learning with interactive simulations is challenging. In this paper, we seek to identify inquiry patterns across topics and evalua ...
Incomplete labels are common in multi-task learning for biomedical applications due to several practical difficulties, e.g., expensive annotation efforts by experts, limit of data collection, different sources of data. A naive approach to enable joint lear ...
During the conceptual design phase of an aircraft manufacturing system, different industrial scenarios need to be evaluated against performance indicators in a collaborative engineering process. Domain experts' knowledge and the motivations for decision-ma ...
Although adults and children differ in self-vs.-other perception, a developmental perspective on this discriminative ability at the brain level is missing. This study examined neural activation for self-vs.-other in a sample of 39 participants spanning fou ...
Reciprocal Peer Tutoring (RPT) is a learning paradigm characteristic of collaborative interaction between learners with alternating tutortutee roles. In recent years, robot-assisted language learning (RALL) has gained traction by its wide application for l ...
Finding optimal bidding strategies for generation units in electricity markets would result in higher profit. However, it is a challenging problem due to the system uncertainty which is due to the lack of knowledge of the strategies of other generation uni ...
Information collected through sensor measurements has the potential to improve knowledge of complex-system behavior, leading to better decisions related to system management. In this situation, and particularly when using digital twins, the quality of sens ...
In this dissertation, we propose multiple methods to improve transfer learning for pretrained language models (PLMs). Broadly, transfer learning is a powerful technique in natural language processing, where a language model is first pre-trained on a data-r ...
Self-tracking technologies open new doors to previously unimaginable scenarios. The diagnosis of diseases years in advance, or supporting the health of astronauts on missions to Mars are just some of many example applications. During the COVID-19 pandemic, ...
