Simone Totaro

Reinforcement Learning · 2020

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 17 citations into it
• Artificial Intelligence — 11 citations into it

Whom Simone Totaro trusts overall

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

1. Richard S. Sutton
2. Martin L. Puterman
3. Tom Schaul
4. Alexander L. Strehl
5. Geoffrey E. Hinton
6. Ofir Nachum
7. Junhyuk Oh
8. Satinder Singh
9. Michael L. Littman
10. Wenling Shang

Papers from Simone Totaro's perspective

Ordered by how strongly the researchers Simone Totaro 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. Attention is All you Need (Neural Information Processing Systems)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Hierarchical reinforcement learning for efficient exploration and transfer (2020) — 10 citations