References of "Wehenkel, Louis"
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See detailA new heuristic approach to deal with discrete variables in optimal power flow computations
Capitanescu, Florin ULg; Wehenkel, Louis ULg

in IEEE Power Tech conference (2009, July)

This paper proposes a new heuristic approach to deal with discrete variables in an optimal power flow (OPF). This approach relies on the first order sensitivity of the objective and inequality constraints ... [more ▼]

This paper proposes a new heuristic approach to deal with discrete variables in an optimal power flow (OPF). This approach relies on the first order sensitivity of the objective and inequality constraints with respect to the discrete variables. The impact of a discrete variable change on the objective and inequality constraints is aggregated into a merit function. The proposed approach searches iteratively for better discrete variable settings as long as the problem solution can be improved. We provide numerical results with the proposed approach on four test systems up to 1203 buses and for the OPF problem of active power loss minimization. [less ▲]

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See detailOptimal power flow computations with constraints limiting the number of control actions
Capitanescu, Florin ULg; Rosehart, William; Wehenkel, Louis ULg

in IEEE Power Tech conference (2009, July)

This paper focuses on optimal power flow (OPF) computations in which no more than a pre-specified number of controls are allowed to move. The benchmark formulation of this OPF problem constitutes a mixed ... [more ▼]

This paper focuses on optimal power flow (OPF) computations in which no more than a pre-specified number of controls are allowed to move. The benchmark formulation of this OPF problem constitutes a mixed integer nonlinear programming (MINLP) problem. To avoid the prohibitive computational time required by classical MINLP approaches to provide a (potentially sub-optimal) solution, we propose instead two alternative approaches. The first one consists in reformulating the MINLP problem as a mathematical program with equilibrium constraints (MPEC). The second approach includes in the classical OPF problem a nonlinear constraint which approximates the integral constraint limiting the number of control variables movement. Both approaches are solved by an interior point algorithm (IPA), slightly adapted to the particular characteristics of each approach. We provide numerical results with the proposed approaches on two test systems and for two practical problems: minimum cost to remove thermal congestion, and minimum cost of load curtailment to restore a feasible equilibrium point. [less ▲]

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See detailCoupling optimization and dynamic simulation for preventive-corrective control of voltage instability
Capitanescu, Florin ULg; Van Cutsem, Thierry ULg; Wehenkel, Louis ULg

in IEEE Transactions on Power Systems (2009), 24(2), 796-805

This paper proposes an approach coupling security constrained optimal power flow with time-domain simulation to determine an optimal combination of preventive and corrective controls ensuring a voltage ... [more ▼]

This paper proposes an approach coupling security constrained optimal power flow with time-domain simulation to determine an optimal combination of preventive and corrective controls ensuring a voltage stable transition of the system towards a feasible long-term equilibrium, if any of a set of postulated contingencies occurs. A security-constrained optimal power flow is used to adjust the respective contribution of preventive and corrective actions. Furthermore, information is extracted from (quasi steady-state) time-domain simulations to iteratively adjust the set of coupling constraints used by a corrective security constrained optimal power flow until its solution is found dynamically secure and viable. Numerical results are provided on a realistic 55-bus test system. [less ▲]

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See detailFast Multi-Class Image Annotation with Random Subwindows and Multiple Output Randomized Trees
Dumont, Marie; Marée, Raphaël ULg; Wehenkel, Louis ULg et al

in Proc. International Conference on Computer Vision Theory and Applications (VISAPP) (2009, February)

This paper addresses image annotation, i.e. labelling pixels of an image with a class among a finite set of predefined classes. We propose a new method which extracts a sample of subwindows from a set of ... [more ▼]

This paper addresses image annotation, i.e. labelling pixels of an image with a class among a finite set of predefined classes. We propose a new method which extracts a sample of subwindows from a set of annotated images in order to train a subwindow annotation model by using the extremely randomized trees ensemble method appropriately extended to handle high-dimensional output spaces. The annotation of a pixel of an unseen image is done by aggregating the annotations of its subwindows containing this pixel. The proposed method is compared to a more basic approach predicting the class of a pixel from a single window centered on that pixel and to other state-of-the-art image annotation methods. In terms of accuracy, the proposed method significantly outperforms the basic method and shows good performances with respect to the state-of-the-art, while being more generic, conceptually simpler, and of higher computational efficiency than these latter. [less ▲]

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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 ▲]

Detailed reference viewed: 24 (7 ULg)