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Informative sample selection in an active learning (AL) setting helps a machine learning system attain optimum performance with minimum labeled samples, thus reducing annotation costs and boosting performance of computer-aided diagnosis systems in the pres ...
As computational thinking (CT) becomes increasingly acknowledged as an important skill in education, self-directed learning (SDL) emerges as a key strategy for developing this capability. The advent of generative AI (GenAI) conversational agents has disrup ...
Traditional example-based learning methods are often limited by static, expert-created content. Hence, they face challenges in scalability, engagement, and effectiveness, as some learners might struggle to relate to the examples or find them relevant. To a ...
Between the ideal and reality lies the decisive world of the performance gap. This project is conducted within the framework of a Master Thesis at the Industrial Processes and Energy Systems Engineering (IPESE) laboratory of Ecole Polytechnique F´ed´erale ...
Computer systems rely heavily on abstraction to manage the exponential growth of complexity across hardware and software. Due to practical considerations of compatibility between components of these complex systems across generations, developers have favou ...
Informed by longstanding artistic practice, this doctoral thesis approaches entanglements of Swiss coloniality in Brazil and Switzerland under the lens of land, archive, and visuality. The enduring legacies of imperial capitalism in the former Colonia Leop ...
Organic solvents are ubiquitous in industrial and domestic applications from the production of pharmaceuticals to household consumer products. The negative impact of most traditional solvents, especially aprotic types, on the environment, health, and safet ...
Randomized measurement protocols such as classical shadows represent powerful resources for quantum technologies, with applications ranging from quantum state characterization and process tomography to machine learning and error mitigation. Recently, the n ...
We present a new algorithm for imitation learning in infinite horizon linear MDPs dubbed ILARL which greatly improves the bound on the number of trajectories that the learner needs to sample from the environment. In particular, we re- move exploration assu ...
The importance of psychological safety in teams has been demonstrated in different settings. Team performance improves when team climate allows team members to be their authentic selves, to ask questions and raise concerns comfortably. However, it is less ...