Évaluation multiméthode de l’engagement des spectateurs en contexte de jeu social

Le projet vise à comprendre les facteurs qui influencent les spectateurs d’un jeu compétitif à interagir pour influencer le jeu en fonction de leur partisanerie pour l’une des deux équipes sur le terrain. Avec des tests utilisateurs où on recrée l’environnement de jeu, on mesurera physiologiquement ainsi qu’à l’aide d’entrevues, l’intensité de l’engagement que le […]

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Sélection d’un ensemble d’amorçage pour l’apprentissage actif appliqué à la prédiction structurée

L’apprentissage automatique est une tâche d’intelligence artificielle où un algorithme apprend une certaine tâche à partir d’exemples. Ce projet a pour objectif de réduire autant que possible la quantité de tels exemples qui doivent être vus par un algorithme pour atteindre des niveaux de performance acceptables. La raison étant que ces exemples sont souvent produits […]

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Chain Certs: Development of a platform for organizational authenticity certificates creation

Blockchain is a decentralized and immutable data structure. The information stored on blockchain is tamper-resistant, immutable and transparent. Blockchain is an interesting platform for managing digital certificates without a central authority. Because paper certificates can be easily faked or tampered with modern computer skills. Additionally, using a central authority for issuing distributing certificates is inefficient. […]

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MalChain: Run-time detection of malicious virtualized components in Service Function Chains using machine learning

Intern will develop new methodologies based on system level logs to detect malicious activities in virtualized environments. To achieve this goal, intern must review the state-of-the-art and proposes new solutions to overcome the shortcomings of currently existing methodologies and introduce new functionalities. The proposed solutions need to be validated and published based on experimental results. […]

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NLP sentiment analysis for contact and support centers

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 […]

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Determining position, speed and stride length using machine learning with sensor fusion based on ultrawideband local positioning system technology

Sensors that track human movement are becoming more and more popular in all kinds of applications including healthcare, sport and general human movement. However, traditional sensors generally have problems tracking individuals indoors and they are not very accurate when measuring subtle movements. Using innovative technology, new wearable sensors have been developed to track human movement […]

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Better predictions of employee events II

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 […]

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Toronto’s City Diplomacy: Arts, Culture, and Heritage

Our project, Toronto’s City Diplomacy: Arts, Culture, and Heritage, brings together scholars and practitioners in the cultural disciplines to consider how the Greater Toronto and Hamilton Area (GTHA) engages in cultural diplomacy and cultural networks locally and globally. With Hot Docs Canadian International Documentary Festival (Hot Docs) as our non-profit partner, this project examines how […]

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Teaching artificial agents to play complex video games from demonstrations

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 […]

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Jordan Shapes for Deep Learning

The proposed project aims to develop a systematic approach for improving deep-learning-based computer vision systems by augmenting the local pixel data with the global shape data (more specifically, Jordan curves) and by adjusting system architectures to accommodate the augmented input. Three canonical computer vision problems will be investigated in this project. They are respectively image […]

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Automating Configuration Management and Deployment in Large-scale Data Centers Augmented with Edge Data Centers

Data centers are now growing and expanding massively. They are large scale and heterogeneous. In addition, they rely more and more on emerging technologies such as Software Defined Networking (SDN) and Network Functions Virtualization (NFV) with “network softwarization” as their key feature. Moreover, they are now being augmented with edge data centers rooted in concepts […]

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