In this project we aim to automatically learn an augmenter network by using an approximate online bilevel optimization procedure. We plan to learn a augmenter network that generates a distribution of transformations that minimizes the loss on a validation set. By unfolding the gradients of the training loss, we will optimize the loss on validation […]

Le projet consiste à développer des algorithmes permettant de créer des secteurs pour les clients de Fastercom. Afin d’y parvenir, différentes méthodes de Machine Learning seront évaluées et implémentées. Cette création de secteurs permettra d’améliorer la performance des algorithmes de la compagnie en découpant le gros problème d’optimisation de tournées de véhicules en petits problèmes […]

Machine learning (ML) has recently achieved impressive success in many applications. As ML starts to penetrate into safety-critical domains, security/robustness concerns on ML systems have received lots of attention lately. Very surprisingly, recent work has shown that current ML models are vulnerable to adversarial attacks, e.g. by perturbing the input slightly ML models can be […]

Ageing is a global phenomenon, which presents challenges and opportunities for many nations, including Canada, China, and Germany, the foci of the study. In addition to the impact on pensions, health care, the labour market, consumer trends, and social services, the greying population also has far-reaching implications for businesses. As the population ages, changes in […]

Machine learning algorithms are being used in a wide range of applications. It is a branch of computer science where the system can learn from the data and make decisions. Financial fraud is an increasing hazard in the financial industry, and it is important to detect a fraudulent transaction. Machine learning algorithms can be used […]

Our project develops novel machine learning algorithms for interpreting complex, multi-agent scenarios in sports analytics. The collaboration with our industrial partner SPORTLOGiQ will tackle open problems in deep reinforcement learning to build novel capabilities in sports analytics for ice hockey. Deep reinforcement learning is a breakthrough technology with prominent successes in games such as Go […]

In this project, we propose a continual learning approach to face the problem of catastrophic forgetting in online image classification problems. Concretely, we propose a model that learns how to mask a series of general modules in a deep learning architecture, so that generalization emerges through the composition of those modules. This is of vital […]

Fraudulent activities are hard to detect, but they cost financial institutions millions of dollars in monetary losses and legal costs every year. Millions of dollars are being lost in credit transactions as criminals are finding new, more sophisticated ways to conduct financial crime. This research project examines novel ways of detecting fraudulent behavior using powerful […]

Detection of financial fraud is a priority for financial institutions. There are a variety of techniques and models that can be used to address the problem of financial fraud. However, as fraudsters are becoming more inventive and adaptive, they have been able to penetrate the conventional protective methods. This is one of the main reasons […]

This research will provide a prediction of sea conditions at a given location based on measurements from meteorlogic and oceanographic ‘smart’ buoys in the general area. The motivation is to provide redundancy in the measurement of sea conditions for safe navigation within the Halifax Harbour when the main smart buoy in Halifax Harbour fails or […]

Il existe actuellement très peu de données sur le dauphin de Peale qui permettent aux autorités gouvernementales de prendre des décisions éclairées en termes de conservation. Le projet de recherche tente de développer un répertoire photographique du dauphin de Peale que l’on retrouve au sud du Chili, en Patagonie. Le but est d’identifier les individus […]

Bioprocesses are indispensable for the sustainable production of high value chemical compounds from renewable feedstock. In many processes, genetically engineered strains with a modified metabolism are used. Boosting the performance of such a production host can be essential to make a bioprocess profitable. Computational strain design provides methods to identify interventions in the microbial metabolism […]