7 citations · 16 across the 3 of their papers we have counts for
8 papers
Human-level Atari 200x faster
Steven Kapturowski, Víctor Campos, Ray Jiang +4
The task of building general agents that perform well over a wide range of tasks has been an important goal in reinforcement learning since its inception. The problem has been subj…
Beyond Fine-Tuning: Transferring Behavior in Reinforcement Learning
Víctor Campos, Pablo Sprechmann, Steven Hansen +5
Designing agents that acquire knowledge autonomously and use it to solve new tasks efficiently is an important challenge in reinforcement learning. Knowledge acquired during an uns…
Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills
Víctor Campos, Alexander Trott, Caiming Xiong +3
Acquiring abilities in the absence of a task-oriented reward function is at the frontier of reinforcement learning research. This problem has been studied through the lens of empow…
How to Initialize your Network? Robust Initialization for WeightNorm & ResNets
Devansh Arpit, Victor Campos, Yoshua Bengio
Residual networks (ResNet) and weight normalization play an important role in various deep learning applications. However, parameter initialization strategies have not been studied…
Importance Weighted Evolution Strategies
Víctor Campos, Xavier Giro-i-Nieto, Jordi Torres
Evolution Strategies (ES) emerged as a scalable alternative to popular Reinforcement Learning (RL) techniques, providing an almost perfect speedup when distributed across hundreds…
Comparing Fixed and Adaptive Computation Time for Recurrent Neural Networks
Daniel Fojo, Víctor Campos, Xavier Giro-i-Nieto
Adaptive Computation Time for Recurrent Neural Networks (ACT) is one of the most promising architectures for variable computation. ACT adapts to the input sequence by being able to…