Audrey Durand

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Membre Académique Associé
Audrey Durand
Professeure adjointe, Université Laval
Audrey Durand

Audrey Durand est professeure adjointe au département d’informatique et de génie logiciel ainsi qu’au département de génie électrique et de génie informatique de l’Université Laval. Elle se spécialise dans les algorithmes qui apprennent par l’interaction avec leur environnement, soit l’apprentissage par renforcement, et s’intéresse particulièrement à l’application de ces approches au domaine de la santé.



Routine Bandits: Minimizing Regret on Recurring Problems
Hassan Saber, Léo Saci, Odalric-Ambrym Maillard and Audrey Durand
(venue unknown)


Increased responsiveness to punishment of cocaine self-administration after experience with high punishment.
Audrey Durand, Paul Girardeau, Luana Freese and Serge H Ahmed


Pharmacists' perceptions of a machine learning model for the identification of atypical medication orders.
Sophie-Camille Hogue, Flora Chen, Geneviève Brassard, Denis Lebel, Jean-François Bussières, Audrey Durand and Maxime Thibault
Journal of the American Medical Informatics Association
Exploring polypharmacy with artificial intelligence: data analysis protocol.
Caroline Sirois, Richard Khoury, Audrey Durand, Pierre-Luc Deziel, Olga Bukhtiyarova, Yohann Chiu, Denis Talbot, Alexandre Bureau, Philippe Després, Christian Gagné, François Laviolette, Anne-Marie Savard, Jacques Corbeil, Thierry Badard, Sonia Jean and Marc Simard
BMC Medical Informatics and Decision Making


Challenges in Statistical Analysis of Data Collected by a Bandit Algorithm: An Empirical Exploration in Applications to Adaptively Randomized Experiments.
Joseph Jay Williams, Jacob Nogas, Nina Deliu, Hammad Shaikh, Sofia S. Villar, Audrey Durand and Anna N. Rafferty
arXiv preprint arXiv:2103.12198


Comparison of pharmacist evaluation of medication orders with predictions of a machine learning model.
Sophie-Camille Hogue, Flora Chen, Geneviève Brassard, Denis Lebel, Jean-François Bussières, Audrey Durand and Maxime Thibault
arXiv preprint arXiv:2011.01925


MICRA-Net: MICRoscopy Analysis Neural Network to solve detection, classification, and segmentation from a single simple auxiliary task
Flavie Lavoie-Cardinal, Anthony Bilodeau, Constantin Delmas, Martin Parent, Paul De Koninck and Audrey Durand


Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks
Maxime Wabartha, Audrey Durand, Vincent François-Lavet and Joelle Pineau
IJCAI 2020
Deep interpretability for GWAS.
Deepak Sharma, Audrey Durand, Marc-André Legault, Louis-Philippe Lemieux Perreault, Audrey Lemaçon, Marie-Pierre Dubé and Joelle Pineau
arXiv preprint arXiv:2007.01516
Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study
Vincenzo Forgetta, Julyan Keller-Baruch, Marie Forest, Audrey Durand, Sahir Bhatnagar, John P Kemp, Maria Nethander, Daniel Evans, John A Morris, Douglas P Kiel, Fernando Rivadeneira, Helena Johansson, Nicholas C Harvey, Dan Mellström, Magnus Karlsson, Cyrus Cooper, David M Evans, Robert Clarke, John A Kanis, Eric Orwoll... (6 more)
PLOS Medicine


Old Dog Learns New Tricks: Randomized UCB for Bandit Problems
Sharan Vaswani, Abbas Mehrabian, Audrey Durand and Branislav Kveton


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, Audrey Durand and Luc Lamontagne


Literature Mining for Incorporating Inductive Bias in Biomedical Prediction Tasks (Student Abstract)
Qizhen Zhang, Audrey Durand and Joelle Pineau
AAAI 2020


Attraction-Repulsion Actor-Critic for Continuous Control Reinforcement Learning
Thang Doan, Bogdan Mazoure, Audrey Durand, Joelle Pineau and R Devon Hjelm
arXiv preprint arXiv:1909.07543


Leveraging Observations in Bandits: Between Risks and Benefits
Andrei Lupu, Audrey Durand and Doina Precup
AAAI 2019
On-line Adaptative Curriculum Learning for GANs
Thang Doan, João Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau and R. Devon Hjelm


Leveraging exploration in off-policy algorithms via normalizing flows.
Bogdan Mazoure, Thang Doan, Audrey Durand, R. Devon Hjelm and Joelle Pineau


Contextual Bandits for Adapting Treatment in a Mouse Model of de Novo Carcinogenesis
Audrey Durand, Charis Achilleos, Demetris Iacovides, Katerina Strati, Georgios D. Mitsis and Joelle Pineau
Machine Learning for Healthcare Conference
Temporal Regularization in Markov Decision Process
arXiv preprint arXiv:1811.00429


Machine Learning to Predict Osteoporotic Fracture Risk from Genotypes
Vincenzo Forgetta, Julyan Keller-Baruch, Marie Forest, Audrey Durand, Sahir Bhatnagar, John Kemp, John A Morris, John A Kanis, Douglas P Kiel, Eugene V McCloskey, Fernando Rivadeneira, Helena Johannson, Nicholas Harvey, Cyrus Cooper, David M Evans, Joelle Pineau, William D Leslie, Celia Mt Greenwood and J Brent Richards


Leveraging Observational Learning for Exploration in Bandits
Andrei Lupu, Audrey Durand and Doina Precup
AAMAS 2018


Genomic Prediction of Osteoporosis Using 426,000 Individuals from UK Biobank
Vincenzo Forgetta, Julyan Keller-Baruch, Marie Forest, Audrey Durand, Sahir Bhatnagar, John Kemp, John Morris, John Kanis, Douglas Kiel, Eugene Mccloskey, Helena Johansson, Nicholas Harvey, Dave Evans, Joelle Pineau, William Leslie, Celia M. T. Greenwood and J. Brent Richards
Journal of Bone and Mineral Research
Temporal Regularization for Markov Decision Process
Streaming kernel regression with provably adaptive mean, variance, and regularization
Audrey Durand, Odalric-Ambrym Maillard and Joelle Pineau
Journal of Machine Learning Research

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