Sparse Multivariate Polynomial Factorization

Factoring large polynomials is one of the main tools provided by mathematical software packages like Maple. It is used by scientists, engineers and mathematicians directly to simplify and study large formulas. It is also used inside Maple to do other tasks such as solving systems of polynomial equations. This project proposes to dramatically improve the […]

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Modélisation des catégories de blessures en considérant la présence d’un représentant légal

L’estimation des réserves est une tâche qu’un actuaire d’une compagnie d’assurances incendie, accidents et risques divers doit accomplir pour démontrer que sa compagnie est solvable. Avec le développement de la technologie et l’accessibilité à une plus grande disponibilité des données, les approches utilisant t l’information disponible pour chacun des paiements, de chacune des réclamations et […]

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Statistical Machine Learning Framework in Retention and Attrition Modelling

Customer or member retention refers to the ability of a company to retain its customers, and customer attrition, as the counterpart of customer retention, refers to the loss of customers. Developing a more accurate and comprehensible predictive model can help companies like Servus better understand member retention and attrition. This project is aiming at using […]

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Uplift models extension for smart marketing

Insurance companies heavily fund marketing campaigns such as, for instance, customer retention or cross-sell initiatives. Uplift modeling aims at predicting the causal effect of an action such as medical treatment or a marketing campaign on a particular individual by taking into consideration the response to an action. Typically, the result of an uplift model is […]

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Evaluation of Measures to Control and Prevent Clostridium difficile Infection

Clostridium difficile infection (CDI) has become the leading cause of hospital acquired nosocomial diarrhea worldwide. The prolonged hospital stays associated with CDI has enormous impact on the healthcare systems in terms of costs and patient outcomes. While treatment of CDI is an important area for ongoing research, prevention efforts will need to be enhanced to […]

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Automated transaction classification using machine learning algorithm

The procurement process of an organization is key to understand company costs. Organizations gather large amounts of data coming from different sources (e.g. income statement, balance sheet, general ledger lines). This information is heterogeneous in nature as it is a mix of unstructured and structured data. Moreover, it needs to be cleaned and consolidated in […]

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Exploring optimal trading rules in a high-frequency portfolio

Given a set of financial instruments with inherent characteristics at different time intervals, we are interested in finding an optimal trading rule in a high-frequency trading context. A trading rule is defined as a combination of indicators as well as an entry threshold (and potentially other trading parameters). The objective function we are trying to […]

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Advancing an Artificial Intelligence Platform for Crop-Health Monitoring

Plants can respond to changes in their surroundings and can convey precise information about their health state. Ecoation has developed a multi-sensory data acquisition device to capture this information and has been collecting in-field sensor data along with data labels produced by human experts during data collection. In addition, images of various parts of plant […]

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