Elaboration d’un modele de classification permettant d’unifier au sein d’un ensemble taxonomique unique des etiquettes de classes issues de corpus separes. Appliquer Ie nouvel ensemble taxonomique sur l’ensemble des corpus pour finalement obtenir un ensemble unique de documents et d’etiquettes. Le prototype mis au point sera utilise par Ie partenaire dans Ie cadre de son […]

In today’s competitive market, customer service has become essential to any company willing to expand and increase its business. Companies cannot afford to fall short of consumer expectations. With the recent progress in Artificial Intelligence (AI) and the impressive results in different industrial areas, companies are adopting AI techniques for customer service. Most of the […]

In recent years, the emergence of massive temporal data has become a reality in almost all aspects of social life, economic activity, security and defense, and poses a big challenge for existing methods. This project focuses on prediction from temporal data that arise ubiquitously in healthcare, social, industrial and financial fields. Events typically include changes […]

The explosion of popularity of deep learning owes a lot to the success of convolutional neural networks, widely used in diverse fields including computer vision and natural language processing. Recently, the group equivariant convolutional neural network (G-CNN) was introduced, where equivariance of symmetries inherent in the data set is built in the architecture of the […]

Machine learning can be used to predict employee events around retention, promotion or movement. This project explores how to generate better predictions by exploring correlations and exploiting them through features that increase predictive strength. Furthermore, the project explores how to reliably fine-tune the predictive model to a particular data set in the presence of interdependence […]

The goal of this research project is to develop novel technics to teach artificial agents how to play complex video games using reinforcement learning and demonstrations. Namely, we wish to propose a novel approach for learning from demonstrations, in which an agent simultaneously learns a behavior and the corresponding reward signal. This training procedure will […]

Social media and other real-time messaging applications represent valuable sources of real-time information that remain untapped by many service operators. The project is aimed at developing methodology for detecting suspicious and/or abnormal real-time events from textual live data feeds, based on predictive and/or anomaly detection algorithms applied to time series and text features. TRT Canada […]

The objective of this project is to reduce the run time of computationally demanding simulation and modeling tasks at the partner organization. The project involves porting several computer algorithms to massively parallel hardware graphics devices that can be programmed using a widely available development platform. Improvements in performance on these computing tasks have direct implications […]

Computational thinking, i.e., the ability to formalize and solve problems with the assistance of computers, has become crucial in a growing range of jobs. Recent research in education has provided encouraging evidence that the development of computational thinking is the most effective when it is taught in the early childhood, and that game-based learning (GBL) […]

The Societe Generale Bank possesses a network of trading applications which generate the hardware consumption data (CPU, memory and network communication). The main usage of this trading system is to receive/ send orders from the market and/ or the clients or vice versa, and based on these order information, business decisions are made accordingly. The […]

A plethora of business models have encouraged the proliferation and expansion of devices connectivity through network densification through 5G core solution. The complexity of the network as well as its ability to evolve constantly have change the way to secure is operated. Security needs to be based on constant monitoring to detect malicious behavior across […]

Better understanding Drug-Drug interactions (DDIs) is crucial for planning therapies and drugs co-administration. While, considerable efforts are spent in labor-intensive in vivo experiments and time-consuming clinical trials, understanding the pharmacological implications and adverse side-effects for some drug combinations is challenging. The majority of interactions remains undetected until therapies are prescribed to patients. We propose to […]