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Peer Reviewed
See detailLearning to Learn: Assessment of Metacognitive competencies
Frenkel, Stéphanie ULg; Nobile, Debora ULg

in IATED (Ed.) INTED2014 Proceedings (2014, March)

Numerous students are having school difficulties linked to the way they learn. Some authors speak of a “metacognitive deficit”. We refer to a “sleeping potential” instead (Frenkel, 2013, in press; Frenkel ... [more ▼]

Numerous students are having school difficulties linked to the way they learn. Some authors speak of a “metacognitive deficit”. We refer to a “sleeping potential” instead (Frenkel, 2013, in press; Frenkel & Deforge, in press; Frenkel & Nobile, 2013). Be it psychologists, teachers or parents, all wish to develop their skills in order to help these students. This is the case in primary and secondary school. Metacognitive abilities play a central role in learning (e.g., Frenkel & Deforge, in press; Giasson, 2001; Grangeat, 1997; Hessels & Hessels-Schlatter, 2010b; Lumbelli, 2003; Poissant, Poëllhuber & Falardeau, 1994; Rozencwajg, 2003; Veenman, Kok & Blöte, 2005) and thus in successful school learning (Büchel, 2013a, 2013b; Van der Stel & Veenman, 2010; Wang, Haertel & Walberg, 1994). However, studying them requires that we clarify what is meant by “metacognition” and “metacognitive abilities”. In this framework, we developed the EDUCA + project which is intended to provide possible solutions. EDUCA + is based on wide field experience. Its theoretical background is based on a substantial review of the literature. Its objective is to increase the expertise of “front line” field workers by developing specific products such as tools, training courses, services, and a website (Frenkel, in press). This will notably enable them to develop their expertise, detect « sleeping » potential, diagnose, give advice when necessary, intervene (prevention and remediation) and use the tools efficiently. Two types of tools are being designed. On the one hand, assessment tools (tests allowing to put forward the learner’s strengths and weaknesses as well as the scope of his/her “sleeping potential”). On the other hand, intervention tools (short prevention vs. remediation programs). This also includes training courses and services. The creation of a website also aims to reinforce the actions of EDUCA + (personalized access depending on the internaut’s profile: students, parents, professionals). The aim of this paper is to present this research project and its main theoretical background. [less ▲]

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Peer Reviewed
See detailLearning to Learn: Assessment of Metacognitive competencies
Frenkel, Stéphanie ULg; Nobile, Debora ULg

Poster (2014, March)

Facing the rise in requests for consultations related to school learning difficulties as well as requests for tools and additional methods by professional field workers, the EDUCA + project constitutes ... [more ▼]

Facing the rise in requests for consultations related to school learning difficulties as well as requests for tools and additional methods by professional field workers, the EDUCA + project constitutes one of the possible answers. This presentation focuses on one of the project’s goals, which is the creation of a Dynamic Assessment (DA) tailored to primary and secondary school learners. In this perspective, a brief introduction to the EDUCA + project will first be given, then, DA itself will be addressed along three lines: a reminder of its main characteristics, a review of the literature on existing tests, and the variables to evaluate. Finally, the planned perspectives will be presented. [less ▲]

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See detailLearning to play K-armed bandit problems
Maes, Francis ULg; Wehenkel, Louis ULg; Ernst, Damien ULg

in Proceedings of the 4th International Conference on Agents and Artificial Intelligence (ICAART 2012) (2012, February)

We propose a learning approach to pre-compute K-armed bandit playing policies by exploiting prior information describing the class of problems targeted by the player. Our algorithm first samples a set of K ... [more ▼]

We propose a learning approach to pre-compute K-armed bandit playing policies by exploiting prior information describing the class of problems targeted by the player. Our algorithm first samples a set of K-armed bandit problems from the given prior, and then chooses in a space of candidate policies one that gives the best average performances over these problems. The candidate policies use an index for ranking the arms and pick at each play the arm with the highest index; the index for each arm is computed in the form of a linear combination of features describing the history of plays (e.g., number of draws, average reward, variance of rewards and higher order moments), and an estimation of distribution algorithm is used to determine its optimal parameters in the form of feature weights. We carry out simulations in the case where the prior assumes a fixed number of Bernoulli arms, a fixed horizon, and uniformly distributed parameters of the Bernoulli arms. These simulations show that learned strategies perform very well with respect to several other strategies previously proposed in the literature (UCB1, UCB2, UCB-V, KL-UCB and $\epsilon_n$-GREEDY); they also highlight the robustness of these strategies with respect to wrong prior information. [less ▲]

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See detailLearning to Predict End-to-End Network Performance
Liao, Yongjun ULg

Doctoral thesis (2013)

The knowledge of end-to-end network performance is essential to many Internet applications and systems including traffic engineering, content distribution networks, overlay routing, application-level ... [more ▼]

The knowledge of end-to-end network performance is essential to many Internet applications and systems including traffic engineering, content distribution networks, overlay routing, application-level multicast, and peer-to-peer applications. On the one hand, such knowledge allows service providers to adjust their services according to the dynamic network conditions. On the other hand, as many systems are flexible in choosing their communication paths and targets, knowing network performance enables to optimize services by e.g. intelligent path selection. In the networking field, end-to-end network performance refers to some property of a network path measured by various metrics such as round-trip time (RTT), available bandwidth (ABW) and packet loss rate (PLR). While much progress has been made in network measurement, a main challenge in the acquisition of network performance on large-scale networks is the quadratical growth of the measurement overheads with respect to the number of network nodes, which renders the active probing of all paths infeasible. Thus, a natural idea is to measure a small set of paths and then predict the others where there are no direct measurements. This understanding has motivated numerous research on approaches to network performance prediction. Commonly, the success of a prediction system is built on its scalability, efficiency, accuracy and practicability. For network performance prediction, two specific requirements have to be met. First, the prediction system should have a decentralized architecture which allows the natural deployment of the system within a networked application. Second, as different performance metrics are useful for different applications, the prediction system should be general and flexible to deal with various metrics in a unified framework. This thesis presents practical approaches to network performance prediction. There are three main contributions. First, the problem of network performance prediction is formulated as a matrix completion problem where the matrix contains performance measures between network nodes with some of them known and the others unknown and thus to be filled. This new formulation is advantageous in that it is flexible to deal with various metrics in a unified framework, despite their diverse nature. The only requirement is that the matrix to be completed has a low-rank characteristic, which has long been observed in performance matrices constructed from various networks and in various metrics. Second, the matrix completion problem is solved by a novel approach called Decentralized Matrix Factorization by Stochastic Gradient Descent (DMFSGD). The approach requires neither explicit constructions of matrices nor special nodes such as landmarks and central servers. Instead, by letting network nodes exchange messages with each other, matrix factorization is collaboratively and iteratively achieved at all nodes, with each node equally retrieving a number of measurements. The approach is practical in that it is simple, with no infrastructure, and is computationally lightweight, containing only vector operations. Third, instead of the conventional representation of exact metric values, this thesis also investigates coarse performance representations including binary classes (The performance is classified into binary classes of either ``good'' or ``bad''.) and ordinal ratings (The performance is quantized from 1 star to 5 stars.). Such more qualitative than quantitative measures not only fulfill the requirements of many Internet applications, but also reduce the measurement cost and enable a unified treatment of various metrics. In addition, as both class and rating measures can be nicely integrated in the matrix completion framework, the same DMFSGD approach is applicable for their prediction, with little modification required. The resulting prediction system has been extensively evaluated on various publicly-available datasets of two kinds of metrics, namely RTT and ABW. These experiments demonstrate not only the scalability and the accuracy of the DMFSGD approach but also its usability in real Internet applications. In addition, the benefits of predicting performance classes and ratings, rather than their actual values, are demonstrated by a case study on peer selection, a function that is commonly required in a number of network applications. [less ▲]

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See detailLearning to rank with extremely randomized trees
Geurts, Pierre ULg; Louppe, Gilles ULg

in JMLR: Workshop and Conference Proceedings (2011, January), 14

In this paper, we report on our experiments on the Yahoo! Labs Learning to Rank challenge organized in the context of the 23rd International Conference of Machine Learning (ICML 2010). We competed in both ... [more ▼]

In this paper, we report on our experiments on the Yahoo! Labs Learning to Rank challenge organized in the context of the 23rd International Conference of Machine Learning (ICML 2010). We competed in both the learning to rank and the transfer learning tracks of the challenge with several tree-based ensemble methods, including Tree Bagging, Random Forests, and Extremely Randomized Trees. Our methods ranked 10th in the first track and 4th in the second track. Although not at the very top of the ranking, our results show that ensembles of randomized trees are quite competitive for the “learning to rank” problem. The paper also analyzes computing times of our algorithms and presents some post-challenge experiments with transfer learning methods. [less ▲]

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Peer Reviewed
See detailLearning Visual Representations for Interactive Systems
Piater, Justus ULg; Jodogne, Sébastien ULg; Detry, Renaud ULg et al

in 14th International Symposium on Robotics Research (2009)

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See detailLearning Visual Representations for Perception-Action Systems
Piater, Justus ULg; JODOGNE, Sébastien ULg; Detry, Renaud ULg et al

in International Journal of Robotics Research (2011), 30(3), 294-307

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Peer Reviewed
See detailLearning, then Compacting Visual Policies
Jodogne, Sébastien ULg; Piater, Justus ULg

in 7th European Workshop on Reinforcement Learning (2005)

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See detailLearrn-Nett, un réseau pour la formation des enseignants. Une communauté de pratique ?
Lebrun, M.; Deschryver, N.; Charlier, B. et al

in Charnet, Chantal; Ghersi, Claire; Monino, Jean-Louis (Eds.) Le défi de la qualité dans l'enseignement supérieur : vers un changement de paradigme. Actes du XXVe Colloque de l'Association Internationale de Pédagogie Universitaire (AIPU) (2008, May)

Il y a plus de 10 ans, le réseau LEARN-NETT naissait de la rencontre de professeurs en sciences de l’éducation et était financé pendant trois ans, d’abord au niveau belge puis par la Communauté Européenne ... [more ▼]

Il y a plus de 10 ans, le réseau LEARN-NETT naissait de la rencontre de professeurs en sciences de l’éducation et était financé pendant trois ans, d’abord au niveau belge puis par la Communauté Européenne. Leur préoccupation ? Outre la formation aux usages des TIC dans les pratiques de formation, oeuvrer à la qualité de la formation pédagogique des futurs enseignants en les rendant davantage capables de travailler en équipe (apprentissage de la collaboration à distance) et d’assurer leur propre développement professionnel. Un élément particulier ? Le réseau LEARN-NETT est toujours actif. Ce mini-colloque sera décliné en trois parties. (1) Le dispositif pédagogique LEARN-NETT : les lignes de forces restées stables depuis 10 ans et les aspects qui ont évolué en fonction des avancées technopédagogiques. (2) Une des valeurs ajoutées de ce dispositif : la formation des tuteurs. Comment les tuteurs apprennent-ils leur fonction, développent-ils leurs compétences dans ce dispositif ? (3) Les bénéfices pour les différents acteurs de LEARN-NETT (enseignantschercheurs, tuteurs …), les perspectives nouvelles liées aux développements pédagogiques et technologiques, les conditions de survie et de développement d’un tel réseau et l’impact institutionnel d’un tel projet comme catalyseur de l’innovation pédagogique. [less ▲]

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See detailLe leasing financier en Belgique
Kohl, Benoît ULg

in Uniform Law Review = Revue de Droit Uniforme (2011), (1/2), 45-82

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See detailLe leasing financier et son harmonisation par Unidroit
Kohl, Benoît ULg

in Dirix, Eric; Leleu, Yves-Henri (Eds.) Rapports belges au Congrès de l'Académie Internationale de droit comparé (2011)

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See detailLe leasing immobilier - Aspects de droit privé
Kohl, Benoît ULg; Vanwijck, Michèle ULg

in Revue de Droit Immobilier (2000)

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See detailLe leasing immobilier
Kohl, Benoît ULg

Scientific conference (2012, February)

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See detailLeasing immobilier: panorama général
Kohl, Benoît ULg

in Kohl, Benoît (Ed.) Le bail et le leasing immobilier. (2009)

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See detailLeast Construction Cost of FSO Offshore Structures and LNG Gas Carriers
Rigo, Philippe ULg; Matagne, Jérôme ULg; Caprace, Jean-David ULg

in ISOPE, The fifteenth International Offshore and Polar Engineering Conference, Seoul (2005, June 19)

In this paper, scantling optimization a FSO offshore structure and a medium size capacity LNG gas carrier are presented. Optmization is based on the LBR5 least cost optimization package. Main originality ... [more ▼]

In this paper, scantling optimization a FSO offshore structure and a medium size capacity LNG gas carrier are presented. Optmization is based on the LBR5 least cost optimization package. Main originality and advantage is to combine the minimization of the construction cost with the preliminary design stage. The optimum scantling (least cost) is determined at the earliest design stage, this means before the signature of the contract. Cost savings of 5 to 10% are currently recorded. Relevant information on the methodology and applications to a FSO unit and a LNG carrier are presented in the paper. [less ▲]

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See detailLeast Cost and Scantling Optimization at the initial Design Stage of Ships
Rigo, Philippe ULg; Toderan, Catalin

in ICETECH 2000 (2000, September)

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See detailLeast Cost Optimisation of a Medium Capacity Gas Carrier
Rigo, Philippe ULg; Toderan, C.

in COMPIT’03, 2nd Int. EuroConference on Computer and IT Applications in the Maritime Industries,Hamburg, Ed. V. Bertram, 14-17 May 2003 (2003, May)

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See detailLeast cost optimization of a large passenger vessel
Richir, Thomas; Losseau, Nicolas; Pircalabu, Eugen et al

in International Conference on “Advancements in Marine Structures”, (Proceedings of MARSTRUCT’2007), Edt Guedes Soares & Das, Publ: Taylor & Francis Group, UK, 12-14 March 2007 (2007, March)

Detailed reference viewed: 27 (0 ULg)