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See detailLearning from blind tests: residues on grinding stones and flaked stone tools
Rots, Veerle ULiege; Hayes, Elspeth; Cnuts, Dries ULiege et al

Conference (2015, May)

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See detailLearning from Incidents and Incident Reporting: Safety Governance at a Belgian Nuclear Research Center
Rossignol, Nicolas ULiege; Van Oudheusden, Michiel ULiege

in Science, Technology & Human Values (2017), 42

This article examines how incidents are governed in a Belgian Nuclear Research Center by way of an incident reporting system named REX. Drawing on a documentary analysis of incident reports, interviews ... [more ▼]

This article examines how incidents are governed in a Belgian Nuclear Research Center by way of an incident reporting system named REX. Drawing on a documentary analysis of incident reports, interviews and focus groups with personnel, it illustrates how REX enacts a safety governmentality centered on identifying incident causes and culprits. As this governmentality mode obscures the epistemic and political character of incidents, it closes down important opportunities for collective learning about safety and safety governance. It is argued that joint reflection about incidents and resistances towards incident reporting serve as fruitful starting points for a more reflexive safety governance that makes explicit how decisions are made in high-risk contexts. Social scientists can enhance governance of this kind by pointing to different perceptions and evaluations of incidents and by insisting that contending interpretations are confronted and accounted for. [less ▲]

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See detailLearning from Maasmechelen ou la ville comme décor
Dawans, Stéphane ULiege; Houbart, Claudine ULiege

in Pinto da Silva, Madalena (Ed.) EURAU12 Porto | Espaço Público e Cidade Contemporânea: Actas do 6º European Symposium on Research in Architecture and Urban Design (2012)

Detailed reference viewed: 62 (23 ULiège)
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See detailLearning from our European imaging colleagues.
Weissman, Neil J.; Lancellotti, Patrizio ULiege

in JACC. Cardiovascular imaging (2014), 7(6), 639-40

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See detailLearning from positive and unlabeled examples by enforcing statistical significance
Geurts, Pierre ULiege

in JMLR: Workshop and Conference Proceedings (2011, April), 15

Given a finite but large set of objects de- scribed by a vector of features, only a small subset of which have been labeled as ‘positive’ with respect to a class of interest, we consider the problem of ... [more ▼]

Given a finite but large set of objects de- scribed by a vector of features, only a small subset of which have been labeled as ‘positive’ with respect to a class of interest, we consider the problem of characterizing the positive class. We formalize this as the problem of learning a feature based score function that minimizes the p-value of a non parametric statistical hypothesis test. For lin- ear score functions over the original feature space or over one of its kernelized versions, we provide a solution of this problem computed by a one-class SVM applied on a surrogate dataset obtained by sampling subsets of the overall set of objects and representing them by their average feature-vector shifted by the average feature-vector of the original sample of positive examples. We carry out experiments with this method on the prediction of targets of transcription factors in two different organisms, E. Coli and S. Cererevisiae. Our method extends enrichment analysis commonly carried out in Bioinformatics and its results outperform common solutions to this problem. [less ▲]

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See detailLearning from recombinant GH treatment in obesity
Vandeva, S.; Rixhon, M.; Tichomirova, M. A. et al

in Obesity and Metabolism (2009), 5(3/4), 156-166

Obese and untreated growth hormone deficiency (GHD) patients have a number of similar clinical and biological abnormalities. Treatment with recombinant human growth hormone (rhGH) in GHD patients has ... [more ▼]

Obese and untreated growth hormone deficiency (GHD) patients have a number of similar clinical and biological abnormalities. Treatment with recombinant human growth hormone (rhGH) in GHD patients has proven effective in beneficially modulating body composition and certain cardiovascular risk factors, thus leading to the hypothesis that administration of rhGH in obese patients could show similar beneficial results. Hyperinsulinism and increased free fatty acid levels are the main factors causing reduced GH release in the setting of obesity. We reviewed the outcomes of 25 adult and paediatric clinical studies carried out in 1987-2009 that examined the effects of rhGH administration in the obese state. Body composition showed mainly a reduction in visceral abdominal fat, whereas total bodyweight increased or remained unchanged. Effects of rhGH on lipid and carbohydrate metabolic profiles in obese patients were heterogeneous. The increasing burden of obesity on one hand, the absence of definitive medical treatment on the other, give rise to grounds for considering rhGH as a possible therapeutic option if not in the general obese population, at least in patients with higher risk of cardiovascular morbidity and mortality. [less ▲]

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See detailLearning from the Past to Improve Future Resettlement Associated with Climate Change
de Sherbinin, Alex; Castro, Marcia; Gemenne, François ULiege et al

in Science (2011), 334(6055), 456-457

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See detailLearning Grasp Affordance Densities
Detry, Renaud ULiege; Kraft, D.; Kroemer, O. et al

in Paladyn. Journal of Behavioral Robotics (2011), 2(1), 1--17

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See detailLearning in, through, and about participatory technology assessment: The case of nanotechnologies for tomorrow's society (NanoSoc)
Van Oudheusden, Michiel ULiege

in Technology Analysis & Strategic Management (2014)

In participatory technology assessment (pTA), technical and nontechnical communities convene to share their views on a sociotechnical challenge, in an attempt to render technology research and development ... [more ▼]

In participatory technology assessment (pTA), technical and nontechnical communities convene to share their views on a sociotechnical challenge, in an attempt to render technology research and development more socially robust. Taking these commitments to transdisciplinary collaboration and co-construction of technology as entry points, this article describes key tensions that emerged in a Flemish pTA project on nanotechnologies, entitled ‘Nanotechnologies for Tomorrow’s Society’ (NanoSoc). The tensions pertain to how the terms of participation were enacted, the potentially conflicting aims embedded in the project’s mission and methods, the various roles initiating pTA researchers (social scientists) assumed throughout the project’s duration, and the deliberative-democratic rationale that sustains pTA frameworks at large. The article is a response to a pressing question posed to the author by pTA professionals, project participants, and policymakers who ask publics to partake in science and technology decision making: Now that NanoSoc is terminated, what can we learn from it? [less ▲]

Detailed reference viewed: 49 (4 ULiège)
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See detailLearning inclusion-optimal chordal graphs
Auvray, Vincent; Wehenkel, Louis ULiege

in Proceedings of the 24th Conference on Uncertainty in Artificial Intelligence (UAI-08) (2008, July 09)

Chordal graphs can be used to encode dependency models that are representable by both directed acyclic and undirected graphs. This paper discusses a very simple and efficient algorithm to learn the ... [more ▼]

Chordal graphs can be used to encode dependency models that are representable by both directed acyclic and undirected graphs. This paper discusses a very simple and efficient algorithm to learn the chordal structure of a probabilistic model from data. The algorithm is a greedy hill-climbing search algorithm that uses the inclusion boundary neighborhood over chordal graphs. In the limit of a large sample size and under appropriate hypotheses on the scoring criterion, we prove that the algorithm will find a structure that is inclusion-optimal when the dependency model of the data-generating distribution can be represented exactly by an undirected graph. The algorithm is evaluated on simulated datasets. [less ▲]

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See detailLearning Latin: Grammars and Annotations in Latin Papyri
Scappaticcio, Maria Chiara ULiege

Conference (2012, April 14)

Detailed reference viewed: 22 (1 ULiège)
See detailLearning modern languages at school in the European Union
Blondin, Christiane ULiege

Book published by Office for Official Publications of the European Communities (1997)

Detailed reference viewed: 7 (0 ULiège)
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See detailLearning movement patterns in mobile networks: a generic method
François, Jean-Marc; Leduc, Guy ULiege; Martin, Sylvain ULiege

in European Wireless 2004 (2004, February)

Predicting terminals movements in mobile networks is useful for more than one reason, in particular for routing management. A way to do such prediction is to learn the movement patterns of mobile nodes ... [more ▼]

Predicting terminals movements in mobile networks is useful for more than one reason, in particular for routing management. A way to do such prediction is to learn the movement patterns of mobile nodes passing by an access router. In this paper, the information (e.g. layer 2 measurements) related to the different paths followed by mobiles are learned using a hidden Markov model. Simulations have been done using this method and show it can handle different layer~2 signals and collect statistical information when no such signal is available. Furthermore, the method works when no information is available and can be extended so as to guess the timing of the handoffs. [less ▲]

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See detailLearning new names for new stimuli : Making the connection
Thibaut, Jean-Pierre; Comblain, Annick ULiege

Poster (1999, September)

Detailed reference viewed: 89 (2 ULiège)
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See detailLearning Object-specific Grasp Affordance Densities
Detry, Renaud ULiege; Başeski, Emre; Krüger, Norbert et al

in International Conference on Development and Learning (2009)

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See detailLearning Objects and Grasp Affordances through Autonomous Exploration
Kraft, Dirk; Detry, Renaud ULiege; Pugeault, Nicolas et al

in International Conference on Computer Vision Systems (2009)

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See detailLearning of interval and general type-2 fuzzy logic systems using simulated annealing: Theory and practice
Almaraashi, Majid; John, Robert; Hopgood, Adrian ULiege et al

in Information Sciences (2016), 360

This paper reports the use of simulated annealing to design more efficient fuzzy logic systems to model problems with associated uncertainties. Simulated annealing is used within this work as a method for ... [more ▼]

This paper reports the use of simulated annealing to design more efficient fuzzy logic systems to model problems with associated uncertainties. Simulated annealing is used within this work as a method for learning the best configurations of interval and general type-2 fuzzy logic systems to maximize their modeling ability. The combination of simulated annealing with these models is presented in the modeling of four benchmark problems including real-world problems. The type-2 fuzzy logic system models are compared in their ability to model uncertainties associated with these problems. Issues related to this combination between simulated annealing and fuzzy logic systems, including type-2 fuzzy logic systems, are discussed. The results demonstrate that learning the third dimension in type-2 fuzzy sets with a deterministic defuzzifier can add more capability to modeling than interval type-2 fuzzy logic systems. This finding can be seen as an important advance in type-2 fuzzy logic systems research and should increase the level of interest in the modeling applications of general type-2 fuzzy logic systems, despite their greater computational load. [less ▲]

Detailed reference viewed: 26 (4 ULiège)
See detailLearning of Multi-Dimensional, Multi-Modal Features for Robotic Grasping
Detry, Renaud ULiege

Doctoral thesis (2010)

While robots are extensively used in factories, our industry hasn't yet been able to prepare them for working in human environments - for instance in houses or in human-operated factories. The main ... [more ▼]

While robots are extensively used in factories, our industry hasn't yet been able to prepare them for working in human environments - for instance in houses or in human-operated factories. The main obstacle to these applications lies in the amplitude of the uncertainty inherent to the environments humans are used to work in, and in the difficulty in programming robots to cope with it. For instance, in robot-oriented environments, robots can expect to find specific tools and objects in specific places. In a human environment, obstacles may force one to find a new way of holding a tool, and new objects appear continuously and need to be dealt with. As it proves difficult to build into robots the knowledge necessary for coping with uncertain environments, the robotics community is turning to the development of agents that acquire this knowledge progressively and that adapt to unexpected events. This thesis studies the problem of vision-based robotic grasping in uncertain environments. We aim to create an autonomous agent that develops grasping skills from experience, by interacting with objects and with other agents. To this end, we present a 3D object model for autonomous, visuomotor interaction. The model represents grasping strategies along with visual features that predict their applicability. It provides a robot with the ability to compute grasp parameters from visual observations. The agent acquires models interactively by manipulating objects, possibly imitating a teacher. With time, it becomes increasingly efficient at inferring grasps from visual evidence. This behavior relies on (1) a grasp model representing relative object-gripper configurations and their feasibility, and (2) a model of visual object structure, which aligns the grasp model to arbitrary object poses (3D positions and orientations). The visual model represents object edges or object faces in 3D by probabilistically encoding the spatial distribution of small segments of object edges or the distribution of small patches of object surface. A model is learned from a few segmented 3D scans or stereo images of an object. Monte Carlo simulation provides robust estimates of the object's 3D position and orientation in cluttered scenes. The grasp model represents the likelihood of success of relative object-gripper configurations. Initial models are acquired from visual cues or by observing a teacher. Models are then refined autonomously by ``playing' with objects and observing the effects of exploratory grasps. After the robot has learned a few object models, learning becomes a combination of cross-object generalization and interactive experience: grasping strategies are generalized across objects that share similar visual substructures; they are then adapted to new objects through autonomous exploration. The applicability of our model is supported by numerous examples of pose estimates in cluttered scenes, and by a robot platform that shows increasing grasping capabilities as it explores its environment. [less ▲]

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See detailLearning parameters in discrete naive Bayes models by computing fibers of the parametrization map
Auvray, Vincent; Wehenkel, Louis ULiege

in NIPS ´08 Workshop: Algebraic and combinatorial methods in machine learning (2008, December 20)

Discrete Naive Bayes models are usually defined parametrically with a map from a parameter space to a probability distribution space. First, we present two families of algorithms that compute the set of ... [more ▼]

Discrete Naive Bayes models are usually defined parametrically with a map from a parameter space to a probability distribution space. First, we present two families of algorithms that compute the set of parameters mapped to a given discrete Naive Bayes distribution satisfying certain technical assumptions. Using these results, we then present two families of parameter learning algorithms that operate by projecting the distribution of observed relative frequencies in a dataset onto the discrete Naive Bayes model considered. They have nice convergence properties, but their computational complexity grows very quickly with the number of hidden classes of the model. [less ▲]

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See detailLearning Probabilistic Discriminative Models of Grasp Affordances under Limited Supervision
Erkan, Ayse; Kroemer, Oliver; Detry, Renaud ULiege et al

in IEEE/RSJ International Conference on Intelligent Robots and Systems (2010)

Detailed reference viewed: 41 (5 ULiège)