References of "Wehenkel, Louis"
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See detailContent-based Image Retrieval by Indexing Random Subwindows with Randomized Trees
Marée, Raphaël ULg; Geurts, Pierre ULg; Wehenkel, Louis ULg

in IPSJ Transactions on Computer Vision and Applications (2009), 1

We propose a new method for content-based image retrieval which exploits the similarity measure and indexing structure of totally randomized tree ensembles induced from a set of subwindows randomly ... [more ▼]

We propose a new method for content-based image retrieval which exploits the similarity measure and indexing structure of totally randomized tree ensembles induced from a set of subwindows randomly extracted from a sample of images. We also present the possibility of updating the model as new images come in, and the capability of comparing new images using a model previously constructed from a different set of images. The approach is quantitatively evaluated on various types of images and achieves high recognition rates despite its conceptual simplicity and computational efficiency. [less ▲]

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See detailInferring bounds on the performance of a control policy from a sample of one-step system transitions
Fonteneau, Raphaël ULg; Murphy, Susan A.; Wehenkel, Louis ULg et al

in 28th Benelux Meeting on Systems and Control (2009)

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See detailBiomarker discovery in asthma-related inflammation and remodeling.
Quesada Calvo, Florence ULg; Fillet, Marianne ULg; De Seny, Dominique ULg et al

in Proteomics (2009), 9(8), 2163-2170

Asthma is a complex inflammatory disease of airways. A network of reciprocal interactions between inflammatory cells, peptidic mediators, extracellular matrix components, and proteases is thought to be ... [more ▼]

Asthma is a complex inflammatory disease of airways. A network of reciprocal interactions between inflammatory cells, peptidic mediators, extracellular matrix components, and proteases is thought to be involved in the installation and maintenance of asthma-related airway inflammation and remodeling. To date, new proteic mediators displaying significant activity in the pathophysiology of asthma are still to be unveiled. The main objective of this study was to uncover potential target proteins by using surface-enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS) on lung samples from mouse models of allergen-induced airway inflammation and remodeling. In this model, we pointed out several protein or peptide peaks that were preferentially expressed in diseased mice as compared to controls. We report the identification of different five proteins: found inflammatory zone 1 or RELM (FIZZ-1), calcyclin (S100A6), clara cell secretory protein 10 (CC10), Ubiquitin, and Histone H4. [less ▲]

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See detailProtéomique par SELDI-TOF-MS des maladies inflammatoires articulaires: identification des protéines S100 comme protéines d'intérêt
De Seny, Dominique ULg; Ribbens, Clio ULg; Cobraiville, Gaël ULg et al

in Revue Médicale de Liège (2009), 64(Spec No), 29-35

Clinical proteomics is a technical approach studying the entire proteome expressed by cells, tissues or organs. It describes the dynamics of cell regulation by detecting molecular events related to ... [more ▼]

Clinical proteomics is a technical approach studying the entire proteome expressed by cells, tissues or organs. It describes the dynamics of cell regulation by detecting molecular events related to diseases development. Proteomic techniques focus mainly on identification of new biomarkers or new therapeutic targets. It is a multidisciplinary approach using medical, biological, bioanalytical and bioinformatics knowledges. A strong collaboration between these fields allowed SELDI-TOF-MS proteomics studies to be performed at the CHU and the University of Liege, in GIGA-Research facilities. The aim of these studies was driven along three main axes of research related to the identification of biomarkers specific to a studied pathology, to a common biological pathway and, finally, to a treatment response. [less ▲]

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See detailAn Extra-trees-based Automatic Target Recognition Algorithm
Pisane, Jonathan ULg; Marée, Raphaël ULg; Ries, Philippe ULg et al

in To appear in Proc. International Radar Conference (2009)

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See detailWhat is the likely future of real-time transient stability ?
Ernst, Damien ULg; Wehenkel, Louis ULg; Pavella, Mania ULg

in Proceedings of the 2009 IEEE/PES Power Systems Conference & Exposition (PSCE 2009) (2009)

Despite very intensive research efforts in the field of transient stability during the last five decades, the large majority of the derived techniques have hardly moved from the research laboratories to ... [more ▼]

Despite very intensive research efforts in the field of transient stability during the last five decades, the large majority of the derived techniques have hardly moved from the research laboratories to the industrial world and, as a matter of fact, the very large majority of today's control centers do not make use of any real-time transient stability software. On the other hand, along all these years the techniques developed for real-time transient stability have mainly focused on the definition of stability margins and speeding-up techniques rather than on preventive or emergency control strategies. In the light of the above observations, this paper attempts to explain the reasons for lack of industrial interest in real-time transient stability, and also to examine an even more fundamental question, namely: is transient stability, as has been stated many decades ago, still the relevant issue in the context of the new power systems morphology towards more dispersed generation, higher penetration of power electronics, larger and more complex structures, and, in addition, of economic and environmental constraints? Or, maybe, there is a need for techniques different from those developed so far? [less ▲]

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See detailInferring bounds on the performance of a control policy from a sample of trajectories
Fonteneau, Raphaël ULg; Murphy, Susan; Wehenkel, Louis ULg et al

in Proceedings of the IEEE International Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL-09) (2009)

We propose an approach for inferring bounds on the finite-horizon return of a control policy from an off-policy sample of trajectories collecting state transitions, rewards, and control actions. In this ... [more ▼]

We propose an approach for inferring bounds on the finite-horizon return of a control policy from an off-policy sample of trajectories collecting state transitions, rewards, and control actions. In this paper, the dynamics, control policy, and reward function are supposed to be deterministic and Lipschitz continuous. Under these assumptions, a polynomial algorithm, in terms of the sample size and length of the optimization horizon, is derived to compute these bounds, and their tightness is characterized in terms of the sample density. [less ▲]

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See detailPlanning under uncertainty, ensembles of disturbance trees and kernelized discrete action spaces
Defourny, Boris ULg; Ernst, Damien ULg; Wehenkel, Louis ULg

in Proceedings of the IEEE International Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL-09) (2009)

Optimizing decisions on an ensemble of incomplete disturbance trees and aggregating their first stage decisions has been shown as a promising approach to (model-based) planning under uncertainty in large ... [more ▼]

Optimizing decisions on an ensemble of incomplete disturbance trees and aggregating their first stage decisions has been shown as a promising approach to (model-based) planning under uncertainty in large continuous action spaces and in small discrete ones. The present paper extends this approach and deals with large but highly structured action spaces, through a kernel-based aggregation scheme. The technique is applied to a test problem with a discrete action space of 6561 elements adapted from the NIPS 2005 SensorNetwork benchmark. [less ▲]

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See detailA rare-event approach to build security analysis tools when N-k (k > 1) analyses are needed (as they are in large-scale power systems)
Belmudes, Florence ULg; Ernst, Damien ULg; Wehenkel, Louis ULg

in Proceedings of the 2009 IEEE Bucharest PowerTech (2009)

We consider the problem of performing N − k security analyses in large scale power systems. In such a context, the number of potentially dangerous N − k contingencies may become rapidly very large when k ... [more ▼]

We consider the problem of performing N − k security analyses in large scale power systems. In such a context, the number of potentially dangerous N − k contingencies may become rapidly very large when k grows, and so running a security analysis for each one of them is often intractable. We assume in this paper that the number of dangerous N − k contingencies is very small with respect to the number of non-dangerous ones. Under this assumption, we suggest to use importance sampling techniques for identifying rare events in combinatorial search spaces. With such techniques, it is possible to identify dangerous contingencies by running security analyses for only a small number of events. A procedure relying on these techniques is proposed in this work for steady-state security analyses. This procedure has been evaluated on the IEEE 118 bus test system. The results show that it is indeed able to efficiently identify among a large set of contingencies some of the rare ones which are dangerous. [less ▲]

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See detailSupervised learning of intra-daily recourse strategies for generation management under uncertainties
Cornélusse, Bertrand ULg; Vignal, Gerald; Defourny, Boris ULg et al

in PowerTech, 2009 IEEE Bucharest (2009)

The aim of this work is to design intra-daily recourse strategies which may be used by operators to decide in real-time the modifications to bring to planned generation schedules of a set of units in ... [more ▼]

The aim of this work is to design intra-daily recourse strategies which may be used by operators to decide in real-time the modifications to bring to planned generation schedules of a set of units in order to respond to deviations from the forecasted operating scenario. Our aim is to design strategies that are interpretable by human operators, that comply with real-time constraints and that cover the major disturbances that may appear during the next day. To this end we propose a new framework using supervised learning to infer such recourse strategies from simulations of the system under a sample of conditions representing possible deviations from the forecast. This framework is validated on a realistic generation system of medium size. [less ▲]

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See detailBounds for Multistage Stochastic Programs using Supervised Learning Strategies
Defourny, Boris ULg; Ernst, Damien ULg; Wehenkel, Louis ULg

in Watanabe, Osamu; Zeugmann, Thomas (Eds.) Stochastic Algorithms: Foundations and Applications (2009)

We propose a generic method for obtaining quickly good upper bounds on the minimal value of a multistage stochastic program. The method is based on the simulation of a feasible decision policy ... [more ▼]

We propose a generic method for obtaining quickly good upper bounds on the minimal value of a multistage stochastic program. The method is based on the simulation of a feasible decision policy, synthesized by a strategy relying on any scenario tree approximation from stochastic programming and on supervised learning techniques from machine learning. [less ▲]

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See detailProbability Density Estimation by Perturbing and Combining Tree Structured Markov Networks
Ammar, Sourour; Leray, Philippe; Defourny, Boris ULg et al

in Proc. of ECSQARU '09: 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (2009)

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See detailReinforcement learning versus model predictive control: a comparison on a power system problem
Ernst, Damien ULg; Glavic, Mevludin; Capitanescu, Florin ULg et al

in IEEE Transactions on Systems, Man & Cybernetics : Part B (2009), 33(2), 517-519

This paper compares reinforcement learning (RL) with model predictive control (MPC) in a unified framework and reports experimental results of their application to the synthesis of a controller for a ... [more ▼]

This paper compares reinforcement learning (RL) with model predictive control (MPC) in a unified framework and reports experimental results of their application to the synthesis of a controller for a nonlinear and deterministic electrical power oscillations damping problem. Both families of methods are based on the formulation of the control problem as a discrete-time optimal control problem. The considered MPC approach exploits an analytical model of the system dynamics and cost function and computes open-loop policies by applying an interior-point solver to a minimization problem in which the system dynamics are represented by equality constraints. The considered RL approach infers in a model-free way closed-loop policies from a set of system trajectories and instantaneous cost values by solving a sequence of batch-mode supervised learning problems. The results obtained provide insight into the pros and cons of the two approaches and show that RL may certainly be competitive with MPC even in contexts where a good deterministic system model is available. [less ▲]

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See detailConstraint Based Learning of Mixtures of Trees
Schnitzler, François ULg; Wehenkel, Louis ULg

Conference (2009)

Mixtures of trees can be used to model any multivariate distributions. In this work the possibility to learn these models from data by causal learning is explored. The algorithm developed aims at ... [more ▼]

Mixtures of trees can be used to model any multivariate distributions. In this work the possibility to learn these models from data by causal learning is explored. The algorithm developed aims at approximating all first order relationships between pairs of variables by a mixture of a given size. This approach is evaluated based on synthetic data, and seems promising. [less ▲]

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See detailPseudo-geographical representations of power system buses by multidimensional scaling
Belmudes, Florence ULg; Ernst, Damien ULg; Wehenkel, Louis ULg

in Proceedings of the 15th International Conference on Intelligent System Applications to Power Systems (ISAP 2009) (2009)

Graphical representations of power systems are systematically used for planning and operation. The coordinate systems commonly used by Transmission System Operators are static and reflect the geographical ... [more ▼]

Graphical representations of power systems are systematically used for planning and operation. The coordinate systems commonly used by Transmission System Operators are static and reflect the geographical positions of each equipment of the system. We propose in this work to position on a twodimensional map the different buses of a power system in a way such that their coordinates also highlight some other physical information related to them. These pseudo-geographical representations are computed by formulating multidimensional scaling problems which aim at mapping a distance matrix combining both geographical and physical information into a vector of two-dimensional bus coordinates. We illustrate through examples that these pseudo-geographical representations can help to gain insights into the power system physical properties. [less ▲]

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

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 detailLe projet PEGASE
Stubbe, Marc; Karoui, Karim; Van Cutsem, Thierry ULg et al

in Revue E Tijdschrift (2008), (4), 37-41

A group of Transmission System Operators (TSO’s), expert companies and leading research centers in power system analysis and applied mathematics, under the coordination of Tractebel Engineering, has ... [more ▼]

A group of Transmission System Operators (TSO’s), expert companies and leading research centers in power system analysis and applied mathematics, under the coordination of Tractebel Engineering, has joined to develop methodologies and software tools able to monitor, simulate and analyze the European Transmission Network (ETN). This project called PEGASE is part of the 7th Framework Programme of the European Commission. Its budget is about 13 MEUR. It started in September 2008 and will last for 4 years. It will define the architecture, data flows and algorithms of an ETN state estimator making use of emerging technologies like the GPS-synchronized Phasor Measurement Units (PMUs). Giving access to the state of the ETN to each TSO would improve dramatically their coordination provided that new ideas to display huge amounts of ETN data are proposed. This is also part of the research. The static simulation of the ETN requires to take into account the various operating rules and control practices of each national grid. New algorithms will be developed, based on optimization techniques and sound engineering judgment. The dynamic simulation of the ETN is of paramount importance for better control and security assessment of this large-scale system. PEGASE will build a prototype of a simulation engine capable of reproducing all kinds of behavior of the ETN. Such an engine will be designed to play extreme scenarios up to the complete black-out of Europe and its subsequent restoration. It will require algorithmic breakthroughs and advanced computer architecture. It will be embedded in a mock-up of a real time dispatcher training simulator. Simplified dynamic simulation tools, able to run much faster than real time, will be developed for on-line security assessment. If the main challenge of the project remains the size and the heterogeneity of the ETN, special attention will be paid to modeling methodology. Component models have to face the complexity introduced by IT and power electronic technologies presently used in power systems. Standard model libraries reach some limits and a greater modeling flexibility is needed to introduce new devices in software tools or exchange models between operators. [less ▲]

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