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Related publications (29)

Efficient Active Learning for Image Classification and Segmentation using a Sample Selection and Conditional Generative Adversarial Network

Jean-Philippe Thiran

Training robust deep learning (DL) systems for medical image classification or segmentation is challenging due to limited images covering different disease types and severity. We propose an active learning (AL) framework to select most informative samples ...

Springer2018

Understanding the Social Implications of the Digital Transformation: Insights from Four Case Studies on the Role of Social Innovation to Foster Resilience of Society, Electronic Participation

Gianluigi Viscusi, Gianluca Carlo Misuraca

This paper advances further the analysis of previous exploratory research conducted by the authors on how social innovation can foster resilience in a digital governance context. The process of innovation in social policy, as well as the building of resili ...

Springer2018

The Multimodal Study of Blended Learning Using Mixed Sources: Dataset and Challenges of the SpeakUp Case

Denis Gillet, Maria Jesus Rodriguez Triana, Adrian Christian Holzer

Social media applications have been proposed as a tool to complement students’ formal learning experiences, often to increase interactivity and participation. However, evidence regarding the benefits and challenges of such applications is still conflicting ...

CEUR2017

Learning Active Learning from Data

Pascal Fua, Ksenia Konyushkova, Raphael Sznitman

In this paper, we suggest a novel data-driven approach to active learning (AL). The key idea is to train a regressor that predicts the expected error reduction for a candidate sample in a particular learning state. By formulating the query selection proced ...

2017

Active Learning and Proofreading for Delineation of Curvilinear Structures

Pascal Fua, Agata Justyna Mosinska, Jakub Tarnawski

Many state-of-the-art delineation methods rely on supervised machine learning algorithms. As a result, they require manually annotated training data, which is tedious to obtain. Furthermore, even minor classification errors may significantly affect the top ...

2017

A principled approach to the design of collaborative MOOC curricula

Stian Haklev

MOOCs have the potential to benefit from the large number of very diverse learners that participate in courses, but this requires a principled approach to MOOC curriculum development. Courses need to take into consideration the diversity of learner experie ...

2017

Lower Bounds on Active Learning for Graphical Model Selection

Volkan Cevher, Jonathan Mark Scarlett

We consider the problem of estimating the underlying graph associated with a Markov random field, with the added twist that the decoding algorithm can iteratively choose which subsets of nodes to sample based on the previous samples, resulting in an active ...

2017

Beyond ePortfolios: Creating, Exploiting, and Archiving Activity Traces, Learning Outcomes, and Learning Analytics as Personal Shareable Online Spaces

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

The concept of an ePortfolio was introduced in 1999 as an electronic learning record and further developed to overcome the limitation of learning management systems lacking persistent storage for learning artifacts. Nowadays, educational platforms have evo ...

IEEE2017

Experimental evolution of slowed cognitive aging in Drosophila melanogaster

Brian Dennis Hollis

Reproductive output and cognitive performance decline in parallel during aging, but it is unknown whether this reflects a shared genetic architecture or merely the declining force of natural selection acting independently on both traits. We used experiment ...

2017

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