152 citations · 308 across the 30 of their papers we have counts for
8 papers · 1 filter
Contextual Preference Distribution Learning
Benjamin Hudson, Laurent Charlin, Emma Frejinger
Decision-making problems often feature uncertainty stemming from heterogeneous and context-dependent human preferences. To address this, we propose a sequential learning-and-optimi…
Decoupling regularization from the action space
Sobhan Mohammadpour, Emma Frejinger, Pierre-Luc Bacon
Regularized reinforcement learning (RL), particularly the entropy-regularized kind, has gained traction in optimal control and inverse RL. While standard unregularized RL methods r…
Maximum entropy GFlowNets with soft Q-learning
Sobhan Mohammadpour, Emmanuel Bengio, Emma Frejinger +1
Generative Flow Networks (GFNs) have emerged as a powerful tool for sampling discrete objects from unnormalized distributions, offering a scalable alternative to Markov Chain Monte…
Periodic Freight Demand Estimation for Large-scale Tactical Planning
Greta Laage, Emma Frejinger, Gilles Savard
Freight carriers rely on tactical planning to design their service network to satisfy demand in a cost-effective way. For computational tractability, deterministic and cyclic Servi…
Assessing the Impact: Does an Improvement to a Revenue Management System Lead to an Improved Revenue?
Greta Laage, Emma Frejinger, Andrea Lodi +1
Airlines and other industries have been making use of sophisticated Revenue Management Systems to maximize revenue for decades. While improving the different components of these sy…
A language processing algorithm for predicting tactical solutions to an operational planning problem under uncertainty
Emma Frejinger, Eric Larsen
This paper is devoted to the prediction of solutions to a stochastic discrete optimization problem. Through an application, we illustrate how we can use a state-of-the-art neural m…