Concept

Formation à distance

Publications associées (148)

Imitation Learning in Discounted Linear MDPs without exploration assumptions

Volkan Cevher, Efstratios Panteleimon Skoulakis, Luca Viano

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 ...

2024

Revisiting adversarial training for the worst-performing class

Volkan Cevher, Grigorios Chrysos, Thomas Michaelsen Pethick

Despite progress in adversarial training (AT), there is a substantial gap between the topperforming and worst-performing classes in many datasets. For example, on CIFAR10, the accuracies for the best and worst classes are 74% and 23%, respectively. We argu ...

2023

Finding Paths for Explainable MOOC Recommendation: A Learner Perspective

Jibril Albachir Frej, Tatjana Nazaretsky

The increasing availability of Massive Open Online Courses (MOOCs) has created a necessity for personalized course recommendation systems. These systems often combine neural networks with Knowledge Graphs (KGs) to achieve richer representations of learners ...

2023

Supporting Teachers' Orchestration in Robot-mediated Classrooms

Sina Shahmoradi

To bring educational robots to classrooms, we need to consider teachers' self-efficacy and challenges in managing a robot-mediated classroom, and how to support them in overcoming these challenges. Orchestration tools are designed to support teachers by pr ...

EPFL2023

Million-scale data integrated deep neural network for phonon properties of heuslers spanning the periodic table

Changpeng Lin, Hong Zhang, Chen Shen, Yong Zhao

Existing machine learning potentials for predicting phonon properties of crystals are typically limited on a material-to-material basis, primarily due to the exponential scaling of model complexity with the number of atomic species. We address this bottlen ...

NATURE PORTFOLIO2023

A dynamic attractor network model of memory formation, reinforcement and forgetting

Wulfram Gerstner, Chiara Gastaldi, Marta Boscaglia

Empirical evidence shows that memories that are frequently revisited are easy to recall, and that familiar items involve larger hippocampal representations than less familiar ones. In line with these observations, here we develop a modelling approach to pr ...

San Francisco2023

An adapted cascade model to scale primary school digital education curricular reforms and teacher professional development programs

Francesco Mondada, Frédérique Michèle Chessel-Lazzarotto, Barbara Bruno, Laila Abdelsalam El-Hamamsy, Emilie-Charlotte Monnier, Gregory Vivian Raymond Liegeois

Many countries struggle to effectively introduce Digital Education (DE) to all K-12 students as they lack adequately trained teachers. While cascade models of in-service teacher-professional development (PD) can rapidly deploy PD-programs through multiple ...

2023

An Adapted Cascade Model to Scale Primary School Digital Education Curricular Reforms and Teacher Professional Development Programs

Francesco Mondada, Frédérique Michèle Chessel-Lazzarotto, Barbara Bruno, Laila Abdelsalam El-Hamamsy, Emilie-Charlotte Monnier, Gregory Vivian Raymond Liegeois

2023

Emergency adaptation to distance learning: no magic bullet, but where there’s a will, there’s a way

Caroline Pulfrey

Whilst, in many countries, the sudden enforced transfer to large-scale distance learning in state schools as a result of COVID_19 lockdown measures caused turmoil, it also provided an unprecedented opportunity to understand more about key factors associate ...

2022

Meta Transfer Learning for Early Success Prediction in MOOCs

Vinitra Swamy, Mirko Marras

Despite the increasing popularity of massive open online courses (MOOCs), many suffer from high dropout and low success rates. Early prediction of student success for targeted intervention is therefore essential to ensure no student is left behind in a cou ...

ACM2022

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