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Joelle Pineau ¹

Joëlle Pineau, (Joelle Pineau)
a Canadian computer scientist, associate professor at McGill University and lead of Facebook's AI Research lab (FAIR) in Montreal, Quebec ¹. Her research focuses on planning under uncertainty and Bayesian reinforcement learning in the domain of Partially Observable Markov Decision Processes (POMDPs) along with robotics. She received her Ph.D. on Tractable Planning Under Uncertainty in 2004 at Carnegie Mellon University under Geoffrey Gordon and Sebastian Thrun ².

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Selected Publications

David Goddeau, Joelle Pineau (2000). Fast reinforcement learning of dialog strategies. ICASSP 2000
Joelle Pineau, Sebastian Thrun (2002). An integrated approach to hierarchy and abstraction for POMDPs. CMU-RI-TR-02-21, Carnegie Mellon University, pdf
Joelle Pineau, Geoffrey Gordon, Sebastian Thrun (2003). Point-based value iteration: An anytime algorithm for POMDPs. IJCAI 2003, pdf
Joelle Pineau (2004). Tractable Planning Under Uncertainty: Exploiting Structure. Ph.D. thesis, Carnegie Mellon University, pdf
Joelle Pineau, Geoffrey Gordon, Sebastian Thrun (2006, 2011). Anytime Point-Based Approximations for Large POMDPs. Journal of Artificial Intelligence Research, Vol. 27, arXiv:1110.0027
Robert West, Joelle Pineau, Doina Precup (2009). Wikispeedia: An Online Game for Inferring Semantic Distances between Concepts. IJCAI 2009

Mahdi Milani Fard, Joelle Pineau, Csaba Szepesvári (2012). PAC-Bayesian Policy Evaluation for Reinforcement Learning. arXiv:1202.3717
Emmanuel Bengio, Pierre-Luc Bacon, Joelle Pineau, Doina Precup (2015). Conditional Computation in Neural Networks for faster models. arXiv:1511.06297
Mohammad Ghavamzadeh, Shie Mannor, Joelle Pineau, Aviv Tamar (2016). Bayesian Reinforcement Learning: A Survey. arXiv:1609.04436
Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, David Meger (2017). Deep Reinforcement Learning that Matters. arXiv:1709.06560
Peter Henderson, Joshua Romoff, Joelle Pineau (2018). Where Did My Optimum Go?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient Methods. arXiv:1810.02525
Vincent Francois-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau (2018). An Introduction to Deep Reinforcement Learning. arXiv:1811.12560

Emmanuel Bengio, Joelle Pineau, Doina Precup (2020). Interference and Generalization in Temporal Difference Learning. arXiv:2003.06350
Joshua Romoff, Peter Henderson, David Kanaa, Emmanuel Bengio, Ahmed Touati, Pierre-Luc Bacon, Joelle Pineau (2020). TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning? arXiv:2007.02786