23 citations · 80 across the 17 of their papers we have counts for
5 papers · 1 filter
Efficient Planning under Partial Observability with Unnormalized Q Functions and Spectral Learning
Tianyu Li, Bogdan Mazoure, Doina Precup +1
Learning and planning in partially-observable domains is one of the most difficult problems in reinforcement learning. Traditional methods consider these two problems as independen…
Attraction-Repulsion Actor-Critic for Continuous Control Reinforcement Learning
Thang Doan, Bogdan Mazoure, Moloud Abdar +3
Continuous control tasks in reinforcement learning are important because they provide an important framework for learning in high-dimensional state spaces with deceptive rewards, w…
Learning Gaussian Graphical Models with Ordered Weighted L1 Regularization
Cody Mazza-Anthony, Bogdan Mazoure, Mark Coates
We address the task of identifying densely connected subsets of multivariate Gaussian random variables within a graphical model framework. We propose two novel estimators based on…
Leveraging exploration in off-policy algorithms via normalizing flows
Bogdan Mazoure, Thang Doan, Audrey Durand +2
The ability to discover approximately optimal policies in domains with sparse rewards is crucial to applying reinforcement learning (RL) in many real-world scenarios. Approaches su…
Exploring attention mechanism for acoustic-based classification of speech utterances into system-directed and non-system-directed
Atta Norouzian, Bogdan Mazoure, Dermot Connolly +1
Voice controlled virtual assistants (VAs) are now available in smartphones, cars, and standalone devices in homes. In most cases, the user needs to first "wake-up" the VA by saying…