171 citations · 185 across the 4 of their papers we have counts for
4 papers
Recurrent Value Functions
Pierre Thodoroff, Nishanth Anand, Lucas Caccia +2
Despite recent successes in Reinforcement Learning, value-based methods often suffer from high variance hindering performance. In this paper, we illustrate this in a continuous con…
Temporal Regularization in Markov Decision Process
Pierre Thodoroff, Audrey Durand, Joelle Pineau +1
Several applications of Reinforcement Learning suffer from instability due to high variance. This is especially prevalent in high dimensional domains. Regularization is a commonly…
Adversarial Balancing for Causal Inference
Michal Ozery-Flato, Pierre Thodoroff, Matan Ninio +2
Biases in observational data of treatments pose a major challenge to estimating expected treatment outcomes in different populations. An important technique that accounts for these…
Learning Robust Features using Deep Learning for Automatic Seizure Detection
Pierre Thodoroff, Joelle Pineau, Andrew Lim
We present and evaluate the capacity of a deep neural network to learn robust features from EEG to automatically detect seizures. This is a challenging problem because seizure mani…