De plus en plus de forums, tels que Slashdot ou Stack Exchange, pro-posent des systèmes de réputations qui se basent sur le vote collaboratif. Les utilisateurs peuvent ainsi donner un score à chaque message posté selon sa per-tinence ou son utilité. Cependant, ces fonctionnalités de vote sont rarement uti-lisées dans de nombreuses communautés en li...
Despite being extensively studied in the literature, the problem of gender recognition from face images remains difficult when dealing with unconstrained images in a cross-dataset protocol. In this work, we propose a convolutional neural network ensemble model to improve the state-of-the-art accuracy of gender recognition from face images on one of...
t User satisfaction is often considered as the objective that should be achieved by spoken dialogue systems. This is why, the reward function of Spoken Dialogue Systems (SDS) trained by Reinforcement Learning (RL) is often designed to reflect user satisfaction. To do so, the state space representation should be based on features capturing user sati...
In this paper we propose a procedure consisting of a first collection phase of social net- work messages, a subsequent user query selection, and finally a clustering phase, de- fined by extending the density-based DBSCAN algorithm, for performing a geographic and temporal exploration of a collection of items, in order to reveal and map their latent...
This paper uses Big Data and Machine Learning for the real-time management of Internet scale Quality-of-Service Route Optimisation with an overlay network. Based on the collection of data sampled each 2 minutes over a large number of source-destinations pairs, we show that intercontinental Internet Protocol (IP) paths are far from optimal with resp...
Sequentially learning to place items in multi-position displays or lists is a task that can be cast into the multiple-play semi-bandit setting. However, a major concern in this context is when the system cannot decide whether the user feedback for each item is actually exploitable. Indeed, much of the content may have been simply ignored by the use...
Published in Granular Computing
Two important ideas at the core of Zadeh’s seminal contributions to fuzzy logic and approximate reasoning are the notions of granulation and that of possibilistic uncertainty. In this paper, elaborating on the basis of some formal analogy, recently laid bare by the authors, between possibility theory and formal concept analysis, we suggest other br...
La recommandation de points d'intérêts (ou POI), est devenue un problème majeur avec l'émergence des réseaux sociaux (ou LBSN). À la différence des approches de recommandation traditionnelles, les données des LBSN présentent des caractéristiques géographique et temporelle importantes qui limitent les performances des algorithmes traditionnels exist...
Published in Autonomous Agents and Multi-Agent Systems
Achieving fast and accurate collective decisions with a large number of simple agents without relying on a central planning unit or on global communication is essential for developing complex collective behaviors. In this paper, we investigate the speed versus accuracy trade-off in collective decision-making in the context of a binary discriminatio...
This paper summarizes the ChaLearn Looking at People 2016 First Impressions challenge data and results obtained by the teams in the first round of the competition. The goal of the competition was to automatically evaluate five “apparent” personality traits (the so-called “Big Five”) from videos of subjects speaking in front of a camera, by using hu...
