6 citations · 9 across the 4 of their papers we have counts for
4 papers
On the Fundamental Limitations of Dual Static CVaR Decompositions in Markov Decision Processes
Mathieu Godbout, Audrey Durand
It was recently shown that dynamic programming (DP) methods for finding static CVaR-optimal policies in Markov Decision Processes (MDPs) can fail when based on the dual formulation…
ACReL: Adversarial Conditional value-at-risk Reinforcement Learning
M. Godbout, M. Heuillet, S. Chandra +2
In the classical Reinforcement Learning (RL) setting, one aims to find a policy that maximizes its expected return. This objective may be inappropriate in safety-critical domains s…
Predicting Visual Improvement after Macular Hole Surgery: a Cautionary Tale on Deep Learning with Very Limited Data
M. Godbout, A. Lachance, F. Antaki +2
We investigate the potential of machine learning models for the prediction of visual improvement after macular hole surgery from preoperative data (retinal images and clinical feat…
A Robust Self-Learning Method for Fully Unsupervised Cross-Lingual Mappings of Word Embeddings: Making the Method Robustly Reproducible as Well
Nicolas Garneau, Mathieu Godbout, David Beauchemin +2
In this paper, we reproduce the experiments of Artetxe et al. (2018b) regarding the robust self-learning method for fully unsupervised cross-lingual mappings of word embeddings. We…