367 citations · 394 across the 3 of their papers we have counts for
3 papers
Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks
Jesse Farebrother, Joshua Greaves, Rishabh Agarwal +4
Auxiliary tasks improve the representations learned by deep reinforcement learning agents. Analytically, their effect is reasonably well understood; in practice, however, their pri…
Learning to Navigate in Complex Environments
Piotr Mirowski, Razvan Pascanu, Fabio Viola +9
Learning to navigate in complex environments with dynamic elements is an important milestone in developing AI agents. In this work we formulate the navigation question as a reinfor…
Efficient Object Localization Using Convolutional Networks
Jonathan Tompson, Ross Goroshin, Arjun Jain +2
Recent state-of-the-art performance on human-body pose estimation has been achieved with Deep Convolutional Networks (ConvNets). Traditional ConvNet architectures include pooling a…