Audrey Durand

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 47

Top Topics

Association Rules

Reinforcement Learning

Bayesian Classification

Microscopy Images

Top Venues

AAAI Fall Symposia

Comput. Electron. Agric.

Publications

Randy Lefebvre, Audrey Durand
On shallow planning under partial observability. CoRR (2024)
Maxime Heuillet, Ola Ahmad, Audrey Durand
Neural Active Learning Meets the Partial Monitoring Framework. CoRR (2024)
Maxime Heuillet, Ola Ahmad, Audrey Durand
Randomized Confidence Bounds for Stochastic Partial Monitoring. CoRR (2024)
Yasmeen Hitti, Ionelia Buzatu, Manuel Del Verme, Mark Lefsrud, Florian Golemo, Audrey Durand
GrowSpace: A reinforcement learning environment for plant architecture. Comput. Electron. Agric. 217 (2024)
François-Alexandre Tremblay, Audrey Durand, Michael Morin, Philippe Marier, Jonathan Gaudreault
Deep reinforcement learning for continuous wood drying production line control. Comput. Ind. 154 (2024)
Dorra Rakia Allegue, Despoina Petsani, Nathalie Ponthon, Evdokimos I. Konstantinidis, Panagiotis D. Bamidis, Eva Kehayia, Audrey Durand, Sara Ahmed
Data harmonization for Advancing research on Personalized Rehabilitation Interventions for Patients with Traumatic Brain Injury and Stroke: A proof of concept. PETRA (2024)
Théophile Berteloot, Richard Khoury, Audrey Durand
Association Rules Mining with Auto-Encoders. CoRR (2023)
Charles Bourbeau, Audrey Durand
Latent Space Evolution under Incremental Learning with Concept Drift (Student Abstract). AAAI (2023)
Rupali Bhati, Jennifer Jones, Audrey Durand
Interpret Your Care: Predicting the Evolution of Symptoms for Cancer Patients. CoRR (2023)
Anthony Bilodeau, Constantin V. L. Delmas, Martin Parent, Paul De Koninck, Audrey Durand, Flavie Lavoie-Cardinal
Microscopy analysis neural network to solve detection, enumeration and segmentation from image-level annotations. Nat. Mach. Intell. 4 (5) (2022)
Alexandre Larouche, Audrey Durand, Richard Khoury, Caroline Sirois
Neural Bandits for Data Mining: Searching for Dangerous Polypharmacy. CoRR (2022)
Mathieu Godbout, Maxime Heuillet, Sharath Chandra Raparthy, Rupali Bhati, Audrey Durand
A Game-Theoretic Perspective on Risk-Sensitive Reinforcement Learning. SafeAI@AAAI (2022)
Anthony Bilodeau, Renaud Bernatchez, Albert Michaud-Gagnon, Flavie Lavoie-Cardinal, Audrey Durand
Contextual bandit optimization of super-resolution microscopy. AI (2022)
Théophile Berteloot, Richard Khoury, Audrey Durand
Cambrian Explosion Algorithm for Multi-Objective Association Rules Mining. CoRR (2022)
Renaud Bernatchez, Audrey Durand, Flavie Lavoie-Cardinal
Annotation Cost-Sensitive Deep Active Learning with Limited Data (Student Abstract). AAAI (2022)
Sophie-Camille Hogue, Flora Chen, Geneviève Brassard, Denis Lebel, Jean-François Bussières, Audrey Durand, Maxime Thibault
Pharmacists' perceptions of a machine learning model for the identification of atypical medication orders. J. Am. Medical Informatics Assoc. 28 (8) (2021)
Yasmeen Hitti, Ionelia Buzatu, Manuel Del Verme, Mark Lefsrud, Florian Golemo, Audrey Durand
GrowSpace: Learning How to Shape Plants. CoRR (2021)
Mathieu Godbout, Maxime Heuillet, Sharath Chandra, Rupali Bhati, Audrey Durand
CARL: Conditional-value-at-risk Adversarial Reinforcement Learning. CoRR (2021)
Caroline Sirois, Richard Khoury, Audrey Durand, Pierre-Luc Déziel, Olga Bukhtiyarova, Yohann Chiu, Denis Talbot, Alexandre Bureau, Philippe Després, Christian Gagné, François Laviolette, Anne-Marie Savard, Jacques Corbeil, Thierry Badard, Sonia Jean, Marc Simard
Exploring polypharmacy with artificial intelligence: data analysis protocol. BMC Medical Informatics Decis. Mak. 21 (1) (2021)
Joseph Jay Williams, Jacob Nogas, Nina Deliu, Hammad Shaikh, Sofia S. Villar, Audrey Durand, Anna N. Rafferty
Challenges in Statistical Analysis of Data Collected by a Bandit Algorithm: An Empirical Exploration in Applications to Adaptively Randomized Experiments. CoRR (2021)
Hassan Saber, Léo Saci, Odalric-Ambrym Maillard, Audrey Durand
Routine Bandits: Minimizing Regret on Recurring Problems. ECML/PKDD (1) (2021)
Nicolas Garneau, Mathieu Godbout, David Beauchemin, Audrey Durand, Luc Lamontagne
A Robust Self-Learning Method for Fully Unsupervised Cross-Lingual Mappings of Word Embeddings: Making the Method Robustly Reproducible as Well. LREC (2020)
Maxime Wabartha, Audrey Durand, Vincent François-Lavet, Joelle Pineau
Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks. IJCAI (2020)
Deepak Sharma, Audrey Durand, Marc-André Legault, Louis-Philippe Lemieux Perreault, Audrey Lemaçon, Marie-Pierre Dubé, Joelle Pineau
Deep interpretability for GWAS. CoRR (2020)
Sharan Vaswani, Abbas Mehrabian, Audrey Durand, Branislav Kveton
Old Dog Learns New Tricks: Randomized UCB for Bandit Problems. AISTATS (2020)
Sophie-Camille Hogue, Flora Chen, Geneviève Brassard, Denis Lebel, Jean-François Bussières, Audrey Durand, Maxime Thibault
Comparison of pharmacist evaluation of medication orders with predictions of a machine learning model. CoRR (2020)
Qizhen Zhang, Audrey Durand, Joelle Pineau
Literature Mining for Incorporating Inductive Bias in Biomedical Prediction Tasks (Student Abstract). AAAI (2020)
Bogdan Mazoure, Thang Doan, Audrey Durand, Joelle Pineau, R. Devon Hjelm
Leveraging exploration in off-policy algorithms via normalizing flows. CoRL (2019)
Bogdan Mazoure, Thang Doan, Audrey Durand, R. Devon Hjelm, Joelle Pineau
Leveraging exploration in off-policy algorithms via normalizing flows. CoRR (2019)
Nicolas Garneau, Mathieu Godbout, David Beauchemin, Audrey Durand, Luc Lamontagne
A Robust Self-Learning Method for Fully Unsupervised Cross-Lingual Mappings of Word Embeddings: Making the Method Robustly Reproducible as Well. CoRR (2019)
Sharan Vaswani, Abbas Mehrabian, Audrey Durand, Branislav Kveton
Old Dog Learns New Tricks: Randomized UCB for Bandit Problems. CoRR (2019)
Andrei Lupu, Audrey Durand, Doina Precup
Leveraging Observations in Bandits: Between Risks and Benefits. AAAI (2019)
Thang Doan, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm
Attraction-Repulsion Actor-Critic for Continuous Control Reinforcement Learning. CoRR (2019)
Thang Doan, João Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm
On-Line Adaptative Curriculum Learning for GANs. AAAI (2019)
Audrey Durand, Charis Achilleos, Demetris Iacovides, Katerina Strati, Georgios D. Mitsis, Joelle Pineau
Contextual Bandits for Adapting Treatment in a Mouse Model of de Novo Carcinogenesis. MLHC (2018)
Louis-Émile Robitaille, Audrey Durand, Marc-André Gardner, Christian Gagné, Paul De Koninck, Flavie Lavoie-Cardinal
Learning to Become an Expert: Deep Networks Applied To Super-Resolution Microscopy. CoRR (2018)
Louis-Émile Robitaille, Audrey Durand, Marc-André Gardner, Christian Gagné, Paul De Koninck, Flavie Lavoie-Cardinal
Learning to Become an Expert: Deep Networks Applied to Super-Resolution Microscopy. AAAI (2018)
Louis-Émile Robitaille, Audrey Durand, Marc-André Gardner, Christian Gagné, Paul De Koninck, Flavie Lavoie-Cardinal
Rating Super-Resolution Microscopy Images With Deep Learning. AAAI (2018)
Pierre Thodoroff, Audrey Durand, Joelle Pineau, Doina Precup
Temporal Regularization in Markov Decision Process. CoRR (2018)
Audrey Durand, Odalric-Ambrym Maillard, Joelle Pineau
Streaming kernel regression with provably adaptive mean, variance, and regularization. J. Mach. Learn. Res. 19 (2018)
Andrei Lupu, Audrey Durand, Doina Precup
Leveraging Observational Learning for Exploration in Bandits. AAMAS (2018)
Thang Doan, João Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm
Online Adaptative Curriculum Learning for GANs. CoRR (2018)
Pierre Thodoroff, Audrey Durand, Joelle Pineau, Doina Precup
Temporal Regularization for Markov Decision Process. NeurIPS (2018)
Audrey Durand, Jean-Alexandre Beaumont, Christian Gagné, Michel Lemay, Sébastien Paquet
Query Completion Using Bandits for Engines Aggregation. CoRR (2017)
Audrey Durand, Odalric-Ambrym Maillard, Joelle Pineau
Streaming kernel regression with provably adaptive mean, variance, and regularization. CoRR (2017)
Audrey Durand, Christian Gagné
Estimating Quality in User-Guided Multi-Objective Bandits Optimization. CoRR (2017)
Julien-Charles Levesque, Audrey Durand, Christian Gagné, Robert Sabourin
Bayesian optimization for conditional hyperparameter spaces. IJCNN (2017)
Audrey Durand, Joelle Pineau
Adaptive Treatment Allocation Using Sub-Sampled Gaussian Processes. AAAI Fall Symposia (2015)
François-Michel De Rainville, Audrey Durand, Félix-Antoine Fortin, Kevin Tanguy, Xavier Maldague, Bernard Panneton, Marie-Josée Simard
Bayesian classification and unsupervised learning for isolating weeds in row crops. Pattern Anal. Appl. 17 (2) (2014)
Audrey Durand, Christian Gagné, Léon Nshimyumukiza, Mathieu Gagnon, François Rousseau, Yves Giguère, Daniel Reinharz
Population-Based Simulation for Public Health: Generic Software Infrastructure and Its Application to Osteoporosis. IEEE Trans. Syst. Man Cybern. Part A 42 (6) (2012)
Julien-Charles Levesque, Audrey Durand, Christian Gagné, Robert Sabourin
Multi-objective evolutionary optimization for generating ensembles of classifiers in the ROC space. GECCO (2012)
Audrey Durand, Christian Gagné, Marc-André Gardner, François Rousseau, Yves Giguère, Daniel Reinharz
SCHNAPS: a generic population-based simulator for public health purposes. SummerSim (2010)