Imitation Learning in Discounted Linear MDPs without exploration assumptions

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

GRE@T-PIONEeR is a Horizon 2020 project coordinated by Chalmers University of Technology, running over the period 2020-2024. 18 university teachers from 8 different universities located in 6 different countries gathered forces to develop and offer advanced ...

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 ...

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 ...

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 ...

Simulation is a powerful approach that plays a significant role in science and technology. Computational models that simulate learner interactions and data hold great promise for educational technology as well. Amongst others, simulated learners can be use ...

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 ...

The learning process depends on the nature of the learning environment, particularly in the case of open-ended learning environments, where the learning process is considered to be non-linear. In this paper, we report on the findings of employing a multimo ...

Long-term monitoring of patients with epilepsy presents a challenging problem from the engineering perspective of real-time detection and wearable devices design. It requires new solutions that allow continuous unobstructed monitoring and reliable detectio ...

This book summarises 15 years of research (2007-2021) on the exploitation of digital technologies for VET. In other words, our activities started the same year as the first iPhone was launched! Four research groups formed the leading house on the topic, na ...

This work proposes a novel strategy for social learning by introducing the critical feature of adaptation. In social learning, several distributed agents update continually their belief about a phenomenon of interest through: i) direct observation of strea ...

The COVID-19 pandemic and the subsequent school closures created several challenges for teachers and students. From one day to the next, teachers had to rethink their educational activities and move to remote learning. Especially with regard to educational ...

Educational Robotics holds the potential to promote the development of important 21st century skills, such as creativity and problem-solving skills in addition to digital literacy. However, the emergence of the Covid-19 pandemic has posed particular obstac ...

Understanding how learners engage with learning technologies, and its relation with their learning, is crucial to the design of effective learning interventions. Assessing the learners’ state however, is non-trivial. Research suggests that performance is n ...

By offering courses and resources, learning platforms on the Web have been attracting lots of participants, and the interactions with these systems have generated a vast amount of learning-related data. Their collection, processing and analysis have promot ...

Federated Learning (FL) is very appealing for its privacy benefits: essentially, a global model is trained with updates computed on mobile devices while keeping the data of users local. Standard FL infrastructures are however designed to have no energy or ...

The ever-growing number of edge devices (e.g., smartphones) and the exploding volume of sensitive data they produce, call for distributed machine learning techniques that are privacy-preserving. Given the increasing computing capabilities of modern edge de ...

Computational thinking courses are no longer exclusive to engineering and computer science students in higher education but have become a requirement in other fields, as well as for students in secondary, primary, and even early childhood education. Comput ...

The large-scale and granular interaction data collected in online learning platforms such as massive open online courses (MOOCs) provide unique opportunities to better understand individuals' learning processes and could facilitate the design of personaliz ...

In this paper, we develop a stochastic-gradient learning algorithm for situations involving streaming data that arise from an underlying clustered structure. In such settings, the variance of gradient noise can be decomposed into the in-cluster variance si ...

Research on Computer-Supported Collaborative Learning (CSCL) has provided significant insights into why collaborative learning is effective and how we can effectively provide support for it. Building on this knowledge, we can investigate when collaboration ...

Imitation Learning in Discounted Linear MDPs without exploration assumptions

Chattez avec Graph Search

Enhancing higher education through hybrid and flipped learning: Experiences from the GRE@T-PIONEeR project

Finding Paths for Explainable MOOC Recommendation: A Learner Perspective

Revisiting adversarial training for the worst-performing class

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

Simulated Learners in Educational Technology: A Systematic Literature Review and a Turing-like Test

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

Temporal Pathways to Learning: How Learning Emerges in an Open-ended Collaborative Activity

Multi-Centroid Hyperdimensional Computing Approach for Epileptic Seizure Detection

Educational Technologies for Vocational Education. Experiences as Digital Clay

Adaptive Social Learning

Designing Tools and Activities for Educational Robotics in Online Learning

Accessible Maker-based Approaches to Educational Robotics in Online Learning

Many Are The Ways to Learn: Identifying multi-modal behavioral profiles of collaborative learning in constructivist activities

L2D 2021: First International Workshop on Enabling Data-Driven Decisions from Learning on the Web

FLeet: Online Federated Learning via Staleness Awareness and Performance Prediction

Private and Secure Distributed Learning

Bringing Computational Thinking to non-STEM Undergraduates through an Integrated Notebook Application

Discovery and Temporal Analysis of MOOC Study Patterns

Cover: A Cluster-Based Variance Reduced Method For Online Learning

It is not either or: An initial investigation into combining collaborative and individual learning using an ITS