79 citations · 230 across the 11 of their papers we have counts for
12 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…
Recurrent Neural Networks for Semantic Instance Segmentation
Amaia Salvador, Miriam Bellver, Victor Campos +4
We present a recurrent model for semantic instance segmentation that sequentially generates binary masks and their associated class probabilities for every object in an image. Our…
More cat than cute? Interpretable Prediction of Adjective-Noun Pairs
Delia Fernandez, Alejandro Woodward, Victor Campos +3
The increasing availability of affect-rich multimedia resources has bolstered interest in understanding sentiment and emotions in and from visual content. Adjective-noun pairs (ANP…
Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks
Victor Campos, Brendan Jou, Xavier Giro-i-Nieto +2
Recurrent Neural Networks (RNNs) continue to show outstanding performance in sequence modeling tasks. However, training RNNs on long sequences often face challenges like slow infer…
Disentangling Motion, Foreground and Background Features in Videos
Xunyu Lin, Victor Campos, Xavier Giro-i-Nieto +2
This paper introduces an unsupervised framework to extract semantically rich features for video representation. Inspired by how the human visual system groups objects based on moti…
From Pixels to Sentiment: Fine-tuning CNNs for Visual Sentiment Prediction
Victor Campos, Brendan Jou, Xavier Giro-i-Nieto
Visual multimedia have become an inseparable part of our digital social lives, and they often capture moments tied with deep affections. Automated visual sentiment analysis tools c…
Diving Deep into Sentiment: Understanding Fine-tuned CNNs for Visual Sentiment Prediction
Victor Campos, Amaia Salvador, Brendan Jou +1
Visual media are powerful means of expressing emotions and sentiments. The constant generation of new content in social networks highlights the need of automated visual sentiment a…