Improving Efficiency and Robustness of Model-based Reinforcement Learning

Model-based reinforcement learning allows AI systems to learn and use predictive models of their environments to plan ahead, achieving tasks more efficiently. The proposed project aims to (i) develop methods for identifying when an uncertain and/or flawed model can be relied on to make plans, and when it cannot, and (ii) implement a method which […]

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Digital Marketing and Sales Decision Optimization

Like many of their global compatriots, Canadian banks have embraced digital transformation, which enables their account holders to access and manage their accounts and investments online, allowing personalized service. This reality includes the needs of internal stakeholders as well as clients. Planning and implementation of Customer Relations Management and digital sales systems require new ways […]

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Development of a supervised and transparent prediction model for predicting bond credit rating migrations in real-time for short to moderate time frame

The purpose of this research is to develop a supervised prediction model that will be used to predict whether a bond credit rating will migrate down to a lower credit rating in a short to moderate time frame. The problem will consist of the development and optimization of a bond credit-rating migration prediction model; the […]

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Traitement du langage et Résumé automatique de documents

Un résumé est un texte qui décrit de façon synthétique la forme, le contenu, et la thèse principale d’un ensemble de document. Une société comme la Fédération des caisses Desjardins reçoit énormément d’informations provenant de ses membres et clients, notamment via les sondages de satisfaction. Grâce à différentes méthodes de traitement automatique du langage nous […]

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Technologies innovantes pour une intelligence urbaine au service des citoyens

Le présent programme de R-D a pour objectif de développer des solutions novatrices – innovations technologiques et sociales – au sein d’un environnement interdisciplinaire (sciences urbaines) et plurisectoriel (université – entreprises – villes). Les projets se réaliseront dans le cadre d’un nouveau programme de maitrise sur mesure en intelligence urbaine chapeauté par la Faculté des […]

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Modeling Exfiltration Events in Sunlife Cybersecurity Data

Many governments and other organizations hold confidential data. Theft of that data can be extremely damaging both to the organization and to the people whose data has been stolen. Massive breaches each involving millions of people have been occurring on a regular basis in recent years. New Cyber Security tools are needed to help people […]

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A Machine Learning based approach for Portfolio Allocation

The goal of this project is to create new algorithms and state-of-the-art methods for resource allocation in a financial context. This model can be applied to other domains, such as fleet and personnel management, scheduling of computer programs, manufacturing production control or controlling a mobile telecommunication network. Alpine Macro provides market insights, investment strategy and […]

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Climate volatility and its impact on baseline trends, natural variability, productivity, and disaster potential in the Canadian ecozones

This project is designed to assess both natural variability and the future change of forest productivity and natural disaster risks that are related to climate. These areas are important to study as climatic change is projected to impact northern latitudes more strongly and disasters, such as floods, droughts, and fires, are predicted to increasingly impact […]

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Investigating multi-task learning in semantic parsing

Current research in semantic parsing suffers from lack of annotated data, which is hard to acquire. In this project, we aim at tackling the problem of converting natural language utterances to SQL language (Text-to-SQL) on complex databases in a low-resource environment. More specifically, we focus on the research of how multi-task learning (MTL) can help […]

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Goal-oriented Safety-Guided Design and Assurance for FinTech

With the increasing popularity of digital assets such as cryptocurrencies, many financial technology (FinTech) systems have become safety critical. However, current FinTech system development approaches often lack the rigorous safety practices found in the aerospace, nuclear, automotive, and military industries. To address safety concerns of FinTech stakeholders (users, but also regulators and financial institutions), this […]

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Assessing the effectiveness of customer management efforts on profitability in the insurance industry

To have a strategic advantage over competitors, companies have been encouraged to adopt customer-centric, value added processes and capabilities. Firms allocate resources to train their employees in the necessary skills to build and maintain healthy relationships with their customers, yet little is understood on how investments in training impacts a firm’s performance. The objective of […]

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Sentiment Analysis for the Assessment of Financial Fitness (SAFF)

We apply Artificial Intelligence (AI) on Sentiment Analysis for the Assessment of Financial Fitness (SAFF), which can help an individual to understand one’s latent feeling and reservation towards money saving, spending and planning. The SAFF framework can be applied to not only financial institutions, but also other sectors, e.g. healthcare, rehabilitation and education. Sentiment analysis […]

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