113 citations · 1k across the 66 of their papers we have counts for
3 papers · 1 filter
Orthogonal Gradient Descent for Continual Learning
Mehrdad Farajtabar, Navid Azizan, Alex Mott +1
Neural networks are achieving state of the art and sometimes super-human performance on learning tasks across a variety of domains. Whenever these problems require learning in a co…
Cross-View Policy Learning for Street Navigation
Ang Li, Huiyi Hu, Piotr Mirowski +1
The ability to navigate from visual observations in unfamiliar environments is a core component of intelligent agents and an ongoing challenge for Deep Reinforcement Learning (RL).…
Improved Knowledge Distillation via Teacher Assistant
Seyed-Iman Mirzadeh, Mehrdad Farajtabar, Ang Li +3
Despite the fact that deep neural networks are powerful models and achieve appealing results on many tasks, they are too large to be deployed on edge devices like smartphones or em…