Katia Estabridis

Reinforcement Learning · 2019

A researcher in the Science corpus: 1 paper; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 38 citations into it
• Artificial Intelligence — 30 citations into it

Whom Katia Estabridis trusts overall

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

1. Richard S. Sutton
2. Ronald J. Williams
3. Jakob N. Foerster
4. G. Tesauro
5. Volodymyr Mnih
6. David Silver
7. Geoffrey E. Hinton
8. Andrew Barto
9. Diederik P. Kingma
10. Yoshua Bengio

Papers from Katia Estabridis's perspective

Ordered by how strongly the researchers Katia Estabridis 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. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
4. Gradient-based learning applied to document recognition
5. Reinforcement Learning: An Introduction
6. Long Short-Term Memory
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Asynchronous Methods for Deep Reinforcement Learning
9. Human-level control through deep reinforcement learning
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• CESMA: Centralized Expert Supervises Multi-Agents (2019) — 6 citations