Bruno Lacerda

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 10 citations into it
• Management Science and Operations Research — 9 citations into it

Whom Bruno Lacerda trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Yinlam Chow
2. David Silver
3. Aviv Tamar
4. Richard S. Sutton
5. Arthur Guez
6. Andrew Barto
7. Sylvain Gelly
8. Michael O. Duff
9. Shie Mannor
10. Brendan O'Donoghue

Papers from Bruno Lacerda's perspective

Ordered by how strongly the researchers Bruno Lacerda trusts endorse each paper. Same corpus, a different order for every researcher.

1. Reinforcement Learning: An Introduction
2. Human-level control through deep reinforcement learning
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
8. Long Short-Term Memory
9. Attention is All you Need (Neural Information Processing Systems)
10. Asynchronous Methods for Deep Reinforcement Learning

Their papers

• Risk-Averse Bayes-Adaptive Reinforcement Learning (2021) — 48 citations