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Publications associées (27)

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

Ali H. Sayed, Bicheng Ying, Kun Yuan

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 ...

IEEE2019

Stimuli-based Gaze Analytics to Enhance Motivation and Learning in MOOCs

Pierre Dillenbourg, Kshitij Sharma

The interaction with the various learners in a Massive Open Online Course (MOOC) is often complex. Contemporary MOOC learning analytics relate with click-streams, keystrokes and other user-input variables. Such variables however, do not always capture lear ...

IEEE2019

Dynamic Average Diffusion With Randomized Coordinate Updates

Ali H. Sayed, Bicheng Ying, Kun Yuan

This work derives and analyzes an online learning strategy for tracking the average of time-varying distributed signals by relying on randomized coordinate-descent updates. During each iteration, each agent selects or observes a random entry of the observa ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2019

Tracing Teacher Collaborative Learning and Innovation Adoption: a Case Study in an Inquiry Learning Platform

Denis Gillet, Maria Jesus Rodriguez Triana, Luis Pablo Prieto Santos

Social processes play an important role in teachers' ongoing professional learning: through interactions with peers and experts to solve problems or co-create materials, teachers internalize knowledge developed in their communities. However, these social p ...

International Society of Learning Sciences2019

Real-world gait speed estimation using wrist sensor: A personalized approach

Kamiar Aminian, Hooman Dejnabadi, Abolfazl Soltani, Martin Savary

Gait speed is an important parameter to characterize people's daily mobility. For real-world speed measurement, inertial sensors or Global Navigation Satellite System (GNSS) can be used on wrist, possibly integrated in a wristwatch. However, power consumpt ...

2019

Small Variance Asymptotics for Non-Parametric Online Robot Learning

Sylvain Calinon, Ajay Kumar Tanwani

Small variance asymptotics is emerging as a useful technique for inference in large scale Bayesian non-parametric mixture models. This paper analyses the online learning of robot manipulation tasks with Bayesian non-parametric mixture models under small va ...

2019

A Blueprint for a Blockchain-Based Architecture to Power a Distributed Network of Tamper-Evident Learning Trace Repositories

Denis Gillet, Maria Jesus Rodriguez Triana, Juan Carlos Farah, Andrii Vozniuk

The need to ensure privacy and data protection in educational contexts is driving a shift towards new ways of securing and managing learning records. Although there are platforms available to store educational activity traces outside of a central repositor ...

2018

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