La plupart des méthodes d'apprentissage par renforcement pour le contrôle adaptatif de la signalisation routière nécessitent une formation partant de zéro po...

Providing the right data to a machine learning model is an important step to insure the performance of the model. Non-compliant training data instances may l...

In this paper, we study a novel approach for data-driven decision-making under uncertainty in the presence of contextual information. Specifically, we addres...

We study how the financial literature has evolved in scale, research team composition, and article topicality across 32 finance-focused academic journals fro...

Recently equal risk pricing, a framework for fair derivative pricing, was extended to consider dynamic risk measures. However, all current implementations ei...

Crew pairing problems (CPP) are regularly solved by airlines to produce crew schedules. The goal of CPPs is to find a set of pairings (sequence of flights a...

The multi-depot scheduling problem (MDVSP) is one of the most studied problem in public transport service planning. It consists of assigning buses to each ti...

We explore the realized alpha-performance heterogeneity in green and brown stocks' universes using the peer performance ratios of Ardia and Boudt(2018). Focu...

A new factor-based representation of implied volatility surfaces is proposed. The factors adequately capture the moneyness and maturity slopes, the smile att...

The transmission of the contagious Coronavirus disease (COVID-19) is highly dependent on individual viral dynamics. Reverse-transcription quantitative polyme...

We investigate the ratio \(\mathcal{I}(G)\) of the average size of a maximal matching to the size of a maximum matching in a graph G. If many maximal mat...

The problem of portfolio management represents an important and challenging class of dynamic decision making problems, where rebalancing decisions need to be...

Optimization with stochastic dominance constraints has recently received an increasing amount of attention in the quantitative risk management literature. In...

Les charges thermostatiques, telles que le chauffage électrique de l'eau et des bâtiments, ont un impact significatif sur la demande en électricité sur une a...

Avec la transition énergétique en cours, les réseaux électriques deviennent de plus en plus complexes et la commande de ceux-ci doit composer avec un accrois...

Le Dixième atelier de résolution de problèmes industriels de Montréal, qui eut lieu du 13 au 27 août 2020, fut organisé conjointement par le Centre de recher...

We propose a tone-based event study to reveal the aggregate abnormal tone dynamics in media articles around earnings announcements. We test whether they co...

The increasingly complex energy systems are turning the attention towards model-free control approaches such as reinforcement learning (RL). This work propos...

Distance metric learning algorithms aim to appropriately measure similarities and distances between data points. In the context of clustering, metric learnin...

Optimal stopping is the problem of deciding the right time at which to take a particular action in a stochastic system, in order to maximize an expected rewa...