Esther Luna Colombini

Reinforcement Learning · with Máximo · 2022

A researcher in the Science corpus: 1 paper; trusts 91 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 57 citations into it
• Artificial Intelligence — 56 citations into it
• Management Science and Operations Research — 17 citations into it
• Computational Theory and Mathematics — 14 citations into it
• Electrical and Electronic Engineering — 10 citations into it
• Control and Systems Engineering — 9 citations into it
• Evaluation & Benchmarks — 9 citations into it

Whom Esther Luna Colombini trusts overall

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

1. Richard S. Sutton
2. Sergey Levine
3. Aviral Kumar
4. Geoffrey E. Hinton
5. Scott Fujimoto
6. Diederik P. Kingma
7. Alex Krizhevsky
8. Yoshua Bengio
9. Justin Fu
10. Doina Precup

Papers from Esther Luna Colombini's perspective

Ordered by how strongly the researchers Esther Luna Colombini 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Reinforcement Learning: An Introduction
8. ImageNet: A large-scale hierarchical image database
9. Human-level control through deep reinforcement learning
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• A Survey on Offline Reinforcement Learning: Taxonomy, Review, and Open Problems (2022) — 424 citations