Strasbourg-Riga : l’Art nouveau aux confins d’empires

Plusieurs ouvrages récents ont montré l’intérêt croissant que le public porte à cette Europe médiane qui a réintégré une Europe à laquelle elle n’avait jamais cessé d’appartenir intellectuellement. L’Art nouveau, qui s’est généralement épanoui dans des villes situées en périphérie d’Empires ou d’États, a fait de ces lieux, jusqu’alors situés à la marge des principales scènes culturelles, de brillants et influents centres artistiques. Malmené par le passé – les années 50 et 60 virent la destru..

SELNET clinical practice guidelines for bone sarcoma

Bone sarcoma are infrequent diseases, representing < 0.2% of all adult neoplasms. A multidisciplinary management within reference centers for sarcoma, with discussion of the diagnostic and therapeutic strategies within an expert multidisciplinary tumour board, is essential for these patients, given its heterogeneity and low frequency. This approach leads to an improvement in patient's outcome, as demonstrated in several studies. The Sarcoma European Latin-American Network (SELNET), aims to improve clinical outcome in sarcoma care, with a special focus in Latin-American countries. These Clinical Practice Guidelines (CPG) have been developed and agreed by a multidisciplinary expert group (including medical and radiation oncologist, surgical oncologist, orthopaedic surgeons, radiologist, pathologist, molecular biologist and representatives of patients advocacy groups) of the SELNET consortium, and are conceived to provide the standard approach to diagnosis, treatment and follow-up of bone sarcoma patients in the Latin-American context

Explaining single predictions : a faster method

International audienceMachine learning has proven increasingly essential in manyfields. Yet, a lot obstacles still hinder its use by non-experts. The lack oftrust in the results obtained is foremost among them, and has inspiredseveral explanatory approaches in the literature. In this paper, we areinvestigating the domain of single prediction explanation. This is per-formed by providing the user a detailed explanation of the attribute'sinfluence on each single predicted instance, related to a particular ma-chine learning model. A lot of possible explanation methods have beendeveloped recently. Although, these approaches often require an impor-tant computation time in order to be efficient. That is why we are inves-tigating about new proposals of explanation methods, aiming to increasetime performances, for a small loss in accuracy

Towards a Multi-Agent Simulation of Cyber-attackers and Cyber-defenders Battles

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Un cadre d'aide à l'exploitation des résultats de prédictions, à destination d'experts de domaine

National audienceL’apprentissage automatique (ML) s’est révélé de plus en plus essentiel dans de nombreux domaines. Pourtant, de nombreux obstacles limitent encore son utilisation par des non-experts. Au premier rang de ceux ci se situe le manque de confiance dans les résultats obtenus et a inspiré plusieurs approches explicatives dans la littérature. Nous proposons ici un cadre pour exploiter cette capacité à expliquer les prédictions de ML de manière simple. Ceci a pour but de permettre aux outils ML existants de fournir une information plus interprétable aux utilisateurs ne maîtrisant pas encore l’apprentissage automatique. Ceci est effectué en fournissant à l’utilisateur une explication détaillée de l’influence des attributs pour chaque instance prédite, en relation avec le modèle d’apprentissage automatique. Nous montrerons également en quoi cette explication aide les utilisateurs non-experts à effectuer certaines tâches d’analyse complexes,telles que la sélection de modèles et l’ingénierie de fonctionnalités, et fournit une assistance pour exploiter efficacement les résultats d’un modèle prédictif

Adaptation des systèmes d'accès à l'information et des documents

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A framework for user assistance on predictive models

International audienceData analysis generally requires very specialized skills, especiallywhen applying machine learning tasks. The ambition of the paperis to propose a framework assisting a domain expert user to analysehis data, in a context of predictive analysis. In particular, the frame-work includes a recommender system for the workflow of analysistasks. Because the lack of explanation in recommendations can leadto loss of confidence, a complementary system is proposed to betterunderstand the predictive models recommended. This complemen-tary system aims to help the user to understand and exploit theresults of the data analysis, by relying on his data expertise. Theframework is validated through a pool of questions and a mock-upshowing the interest of the approach

Personalized Information Access Through Flexible and Interoperable Profiles

International audienceWhen searching information, any user has to face huge cognitive efforts to obtain accurate and relevant results. The search task includes a set of complementary sub-tasks in which the user needs to be necessarily involved. But, the real place of the users is not obvious without an effective knowledge of their context, environment, and so on. So we assume that a better knowledge of the user and of available information should make it possible to implement techniques aimed at adapting the retrieved information contents, as well as the search process itself. This personalization mainly relies on the definition of profiles. Since applications principally manage specific user/information profiles (structure and content), we propose in this paper a generic and a flexible profile model. This latter facilitates the construction and the interoperability of various profiles coming from different applications and/or having different structure/content. This paper presents the way the different resources (user, information...) can be modeled within the information search process and its related tasks. Then, we discuss the usefulness of profiles in such processes/tasks. Finally we present the generic and the flexible profile model we propose