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Discovery and Temporal Analysis of Latent Study Patterns from MOOC Interaction Sequences

Related publications (43)

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Semi-supervised and unsupervised kernel-based novelty detection with application to remote sensing images

Frank Grégoire Jean de Morsier

The main challenge of new information technologies is to retrieve intelligible information from the large volume of digital data gathered every day. Among the variety of existing data sources, the satellites continuously observing the surface of the Earth ...

EPFL2014

Semi-Automatic Transcription Tool for Ancient Manuscripts

Matthieu Martin Jean-André Simeoni

In this work, we investigate various techniques from the fields of shape analysis and image processing in order to construct a semi-automatic transcription tool for ancient manuscripts. First, we design a shape matching procedure using shape contexts, intr ...

2014

With the general technological advances of the recent years, current learning environments amass an abundance of data. Albeit such data offer the chance of better understand the learning process, stakeholders – learners, teachers and institutions – often n ...

2013

Cluster-based prediction of mathematical learning patterns

This paper introduces a method to predict and analyse students' mathematical performance by detecting distinguishable subgroups of children who share similar learning patterns. We employ pairwise clustering to analyse a comprehensive dataset of user intera ...

Springer2013

Active learning deals with developing methods that select examples that may express data characteristics in a compact way. For remote sensing image segmentation, the selected samples are the most informative pixels in the image so that classifiers trained ...

2012

Unsupervised change detection with kernels

Devis Tuia

In this letter, an unsupervised kernel-based approach to change detection is introduced. Nonlinear clustering is utilized to partition in two a selected subset of pixels representing both changed and unchanged areas. Once the optimal clustering is obtained ...

Ieee-Inst Electrical Electronics Engineers Inc2012

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When dealing with change detection problems, information about the nature of the changes is often unavailable. In this paper we propose a solution to perform unsupervised change detection based on nonlinear support vector clustering. We build a series of n ...

2012

We propose a fully-distributed stochastic-gradient strategy based on diffusion adaptation techniques. We show that, for strongly convex risk functions, the excess-risk at every node decays at the rate of O(1/Ni), where N is the number of learners and i is ...

IEEE2012

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We present a longitudinal study on the participation regulation effects in the presence of a speech aware interactive table. This study focuses on training meetings of groups of top level managers, whose compositions do not change, in a corporate organizat ...

Assoc Computing Machinery2012

We live in a rapidly changing digital world marked by technological advances, and fraught with online information constantly growing thanks to the Internet revolution and the online social applications in particular. Formal learning acquired in traditional ...

EPFL2010