8.9k citations · 11.5k across the 56 of their papers we have counts for
5 papers · 1 filter
Meta-Learning with Latent Embedding Optimization
Andrei A. Rusu, Dushyant Rao, Jakub Sygnowski +4
Gradient-based meta-learning techniques are both widely applicable and proficient at solving challenging few-shot learning and fast adaptation problems. However, they have practica…
Meta-Learning by the Baldwin Effect
Chrisantha Thomas Fernando, Jakub Sygnowski, Simon Osindero +6
The scope of the Baldwin effect was recently called into question by two papers that closely examined the seminal work of Hinton and Nowlan. To this date there has been no demonstr…
Mix&Match - Agent Curricula for Reinforcement Learning
Wojciech Marian Czarnecki, Siddhant M. Jayakumar, Max Jaderberg +5
We introduce Mix&Match (M&M) - a training framework designed to facilitate rapid and effective learning in RL agents, especially those that would be too slow or too challenging to…
Massively Parallel Video Networks
Joao Carreira, Viorica Patraucean, Laurent Mazare +2
We introduce a class of causal video understanding models that aims to improve efficiency of video processing by maximising throughput, minimising latency, and reducing the number…
Kickstarting Deep Reinforcement Learning
Simon Schmitt, Jonathan J. Hudson, Augustin Zidek +8
We present a method for using previously-trained 'teacher' agents to kickstart the training of a new 'student' agent. To this end, we leverage ideas from policy distillation and po…