Lorenzo Canese

Reinforcement Learning · 2021

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 34 citations into it
• Artificial Intelligence — 29 citations into it

Whom Lorenzo Canese trusts overall

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

1. Richard S. Sutton
2. Ben J. A. Kröse
3. Yoshua Bengio
4. Sergey Ioffe
5. Geoffrey E. Hinton
6. Ronald J. Williams
7. Jakob N. Foerster
8. David Silver
9. Volodymyr Mnih
10. Sainbayar Sukhbaatar

Papers from Lorenzo Canese's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. ImageNet: A large-scale hierarchical image database
9. Reinforcement Learning: An Introduction
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Multi-Agent Reinforcement Learning: A Review of Challenges and Applications (2021) — 426 citations