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2020 – today
- 2024
[j9]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: 108613 (2024)- [j8]François-Alexandre Tremblay, Audrey Durand, Michael Morin, Philippe Marier, Jonathan Gaudreault:
Deep reinforcement learning for continuous wood drying production line control. Comput. Ind. 154: 104036 (2024) - [c23]Maxime Heuillet, Ola Ahmad, Audrey Durand:
Randomized Confidence Bounds for Stochastic Partial Monitoring. ICML 2024 - [c22]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 - [i22]Maxime Heuillet, Ola Ahmad, Audrey Durand:
Randomized Confidence Bounds for Stochastic Partial Monitoring. CoRR abs/2402.05002 (2024) - [i21]Maxime Heuillet, Ola Ahmad, Audrey Durand:
Neural Active Learning Meets the Partial Monitoring Framework. CoRR abs/2405.08921 (2024) - [i20]Randy Lefebvre, Audrey Durand:
On shallow planning under partial observability. CoRR abs/2407.15820 (2024) - 2023
- [j7]Louis-Philippe Vignault, Audrey Durand, Pascal Germain:
Erratum: Risk Bounds for the Majority Vote: From a PAC-Bayesian Analysis to a Learning Algorithm. J. Mach. Learn. Res. 24: 294:1-294:13 (2023) - [c21]Charles Bourbeau, Audrey Durand:
Latent Space Evolution under Incremental Learning with Concept Drift (Student Abstract). AAAI 2023: 16166-16167 - [i19]Rupali Bhati, Jennifer Jones, Audrey Durand:
Interpret Your Care: Predicting the Evolution of Symptoms for Cancer Patients. CoRR abs/2302.09659 (2023) - [i18]Théophile Berteloot, Richard Khoury, Audrey Durand:
Association Rules Mining with Auto-Encoders. CoRR abs/2304.13717 (2023) - 2022
- [j6]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): 455-466 (2022) - [c20]Renaud Bernatchez, Audrey Durand, Flavie Lavoie-Cardinal:
Annotation Cost-Sensitive Deep Active Learning with Limited Data (Student Abstract). AAAI 2022: 12913-12914 - [c19]Mathieu Godbout, Maxime Heuillet, Sharath Chandra Raparthy, Rupali Bhati, Audrey Durand:
A Game-Theoretic Perspective on Risk-Sensitive Reinforcement Learning. SafeAI@AAAI 2022 - [c18]Anthony Bilodeau, Renaud Bernatchez, Albert Michaud-Gagnon, Flavie Lavoie-Cardinal, Audrey Durand:
Contextual bandit optimization of super-resolution microscopy. Canadian AI 2022 - [i17]Théophile Berteloot, Richard Khoury, Audrey Durand:
Cambrian Explosion Algorithm for Multi-Objective Association Rules Mining. CoRR abs/2211.12767 (2022) - [i16]Alexandre Larouche, Audrey Durand, Richard Khoury, Caroline Sirois:
Neural Bandits for Data Mining: Searching for Dangerous Polypharmacy. CoRR abs/2212.05190 (2022) - 2021
- [j5]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): 1712-1718 (2021) - [j4]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): 219 (2021) - [c17]Hassan Saber, Léo Saci, Odalric-Ambrym Maillard, Audrey Durand:
Routine Bandits: Minimizing Regret on Recurring Problems. ECML/PKDD (1) 2021: 3-18 - [i15]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 abs/2103.12198 (2021) - [i14]Mathieu Godbout, Maxime Heuillet, Sharath Chandra, Rupali Bhati, Audrey Durand:
CARL: Conditional-value-at-risk Adversarial Reinforcement Learning. CoRR abs/2109.09470 (2021) - [i13]Yasmeen Hitti, Ionelia Buzatu, Manuel Del Verme, Mark Lefsrud, Florian Golemo, Audrey Durand:
GrowSpace: Learning How to Shape Plants. CoRR abs/2110.08307 (2021) - 2020
- [c16]Qizhen Zhang, Audrey Durand, Joelle Pineau:
Literature Mining for Incorporating Inductive Bias in Biomedical Prediction Tasks (Student Abstract). AAAI 2020: 13983-13984 - [c15]Sharan Vaswani, Abbas Mehrabian, Audrey Durand, Branislav Kveton:
Old Dog Learns New Tricks: Randomized UCB for Bandit Problems. AISTATS 2020: 1988-1998 - [c14]Maxime Wabartha, Audrey Durand, Vincent François-Lavet, Joelle Pineau:
Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks. IJCAI 2020: 2140-2147 - [c13]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: 5546-5554 - [i12]Deepak Sharma, Audrey Durand, Marc-André Legault, Louis-Philippe Lemieux Perreault, Audrey Lemaçon, Marie-Pierre Dubé, Joelle Pineau:
Deep interpretability for GWAS. CoRR abs/2007.01516 (2020) - [i11]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 abs/2011.01925 (2020)
2010 – 2019
- 2019
- [c12]Thang Doan, João Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm:
On-Line Adaptative Curriculum Learning for GANs. AAAI 2019: 3470-3477 - [c11]Andrei Lupu, Audrey Durand, Doina Precup:
Leveraging Observations in Bandits: Between Risks and Benefits. AAAI 2019: 6112-6119 - [c10]Bogdan Mazoure, Thang Doan, Audrey Durand, Joelle Pineau, R. Devon Hjelm:
Leveraging exploration in off-policy algorithms via normalizing flows. CoRL 2019: 430-444 - [i10]Bogdan Mazoure, Thang Doan, Audrey Durand, R. Devon Hjelm, Joelle Pineau:
Leveraging exploration in off-policy algorithms via normalizing flows. CoRR abs/1905.06893 (2019) - [i9]Thang Doan, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm:
Attraction-Repulsion Actor-Critic for Continuous Control Reinforcement Learning. CoRR abs/1909.07543 (2019) - [i8]Sharan Vaswani, Abbas Mehrabian, Audrey Durand, Branislav Kveton:
Old Dog Learns New Tricks: Randomized UCB for Bandit Problems. CoRR abs/1910.04928 (2019) - [i7]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 abs/1912.01706 (2019) - 2018
- [j3]Audrey Durand, Odalric-Ambrym Maillard, Joelle Pineau:
Streaming kernel regression with provably adaptive mean, variance, and regularization. J. Mach. Learn. Res. 19: 17:1-17:34 (2018) - [c9]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: 7805-7810 - [c8]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: 8141-8142 - [c7]Andrei Lupu, Audrey Durand, Doina Precup:
Leveraging Observational Learning for Exploration in Bandits. AAMAS 2018: 2001-2003 - [c6]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: 67-82 - [c5]Pierre Thodoroff, Audrey Durand, Joelle Pineau, Doina Precup:
Temporal Regularization for Markov Decision Process. NeurIPS 2018: 1784-1794 - [i6]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 abs/1803.10806 (2018) - [i5]Thang Doan, João Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm:
Online Adaptative Curriculum Learning for GANs. CoRR abs/1808.00020 (2018) - [i4]Pierre Thodoroff, Audrey Durand, Joelle Pineau, Doina Precup:
Temporal Regularization in Markov Decision Process. CoRR abs/1811.00429 (2018) - 2017
- [c4]Julien-Charles Levesque, Audrey Durand, Christian Gagné, Robert Sabourin:
Bayesian optimization for conditional hyperparameter spaces. IJCNN 2017: 286-293 - [i3]Audrey Durand, Christian Gagné:
Estimating Quality in User-Guided Multi-Objective Bandits Optimization. CoRR abs/1701.01095 (2017) - [i2]Audrey Durand, Odalric-Ambrym Maillard, Joelle Pineau:
Streaming kernel regression with provably adaptive mean, variance, and regularization. CoRR abs/1708.00768 (2017) - [i1]Audrey Durand, Jean-Alexandre Beaumont, Christian Gagné, Michel Lemay, Sébastien Paquet:
Query Completion Using Bandits for Engines Aggregation. CoRR abs/1709.04095 (2017) - 2015
- [c3]Audrey Durand, Joelle Pineau:
Adaptive Treatment Allocation Using Sub-Sampled Gaussian Processes. AAAI Fall Symposia 2015: 9-11 - 2014
- [j2]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): 401-414 (2014) - 2012
- [j1]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): 1396-1409 (2012) - [c2]Julien-Charles Levesque, Audrey Durand, Christian Gagné, Robert Sabourin:
Multi-objective evolutionary optimization for generating ensembles of classifiers in the ROC space. GECCO 2012: 879-886 - 2010
- [c1]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: 182-189
Coauthor Index
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last updated on 2024-10-07 21:24 CEST by the dblp team
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