PALLEZ , Denis

no abstract

An optimisation problem is said to be expensive if assessing the interest of a candidate solution requires access to very significant resources, or resources that are difficult to mobilise. Such problems severely penalise optimisation methods for finding one or more satisfactory solutions to the problem in a reasonable time or, more generally,...

Dans cette présentation, nous présentons un nouvel algorithme qui minimise la fatigue de l'utilisateur pendant la phase d'évaluation d'un algortihme évolutionnaire interactif en utilisant un oculomètre . Cette approche est appliquée au problème d'optimisation One-Max interactif.

We propose Interactive Differential Evolution (IDE) based on paired comparisons for reducing user fatigue and evaluate its convergence speed in comparison with Interactive Genetic Algorithms (IGA) and two tournament IGA's. User interface and convergence performance are major key points for reducing Interactive Evolutionary Computation (IEC)...

Evolutionary algorithms (EA) are developed and compared based on well defined benchmark problems, but their application to real-world problems is still challenging. In image processing, EA have been used to tune a particular image filter or in the design of filters themselves. But nowadays in digital cameras, the image sensor captures a raw...

We propose Interactive Differential Evolution (IDE) based on paired comparisons for reducing user fatigue and evaluate its convergence speed in comparison with Interactive Genetic Algorithms (IGA) and tournament IGA. User interface and convergence performance are two big keys for reducing Interactive Evolutionary Computation (IEC) user fatigue....

International audience

In this paper, we firstly present what is interactive evolutionary computation (IEC) and rapidly how we have combined this artificial intelligence technique with an eye-tracker for visual optimization. Next, in order to correctly parameterize our application, we present results from applying data mining techniques on gaze information coming...

Genetic regulatory network (GRN) modelling aims at studying and understanding the molecular mechanisms that enable the organism to perform essential functions ranging from metabolism to environmental disturbance adaptation. Studying the dynamics of these systems opens new perspectives with crucial applications in fundamental biology,...

Real-world applications of artificial intelligence often require the decision-maker to choose between multiple optimal solutions at hand before making a final decision. Since there is no guarantee that an increase in the budget or several independent executions will yield different solutions, classic mechanisms are not suitable for identifying...

Multimodal Optimization (MMO) aims at identifying several best solutions to a problem whereas classical optimization converge oftenly to only one good solution. MMO has been an active research area in the past years and several new evolutionary algorithms have been developed to tackle multimodal problems. In this work, we compare extensively...

MicroRNAs, small non-coding elements implied in gene regulation, are very interesting biomarkers for various diseases such as cancers. They represent potential prodigious biotechnologies for early diagnosis and gene therapies. However, experimental verification of microRNA-disease associations are time-consuming and costly, so that...

The identification of condition-specific gene sets from transcriptomic experiments is important to reveal regulatory and signaling mechanisms associated with a given cellular response. Statistical methods of differential expression analysis, designed to assess individual gene variations, have trouble highlighting modules of small varying genes...

In this paper, we propose a new framework hybridizing a Support Vector Machine (SVM), a Multi-Objective Genetic Algorithm (MOGA) and a Locality Sensitive Hashing (LSH). The goal is to tackle fine-grained classification challenges which means classifying many classes with high similarities between classes and poor similarities inside one class....

The amount of images contained in repositories or available on Internet has exploded over the last years. In order to retrieve efficiently one or several images in a database, the development of Content-Based Image Retrieval (CBIR) systems has become an intensively active research area. However, most proposed systems are keyword-based and few...

The study of gene regulatory networks (GRNs) allows us to better understand biological systems such as the adaptation of the organism to a disturbance in the environment. Hybrid GRNs (hGRNs) are of interest because they integrate the continuous time evolution in GRN modeling which is convenient in biology. This study focuses on the problem of...

International audience

Monte-Carlo Tree Search (MCTS) is largely responsible for the improvement not only of many computer games, including Go and General Game Playing (GPP), but also of real-world continuous Markov decision process problems. MCTS initially uses the Upper Confidence bounds applied to Trees (UCT), but the Rapid Action Value Estimation (RAVE) heuristic...