Rasul Tutunov

Reinforcement Learning · 2015–2018

A researcher in the Science corpus: 3 papers; trusts 49 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 50 citations into it
• Artificial Intelligence — 47 citations into it
• Computer Vision and Pattern Recognition — 9 citations into it
• Control and Systems Engineering — 9 citations into it
• Computational Theory and Mathematics — 8 citations into it
• Management Science and Operations Research — 7 citations into it
• Representation & Self-Supervised Learning — 7 citations into it
• Optimization & Training — 5 citations into it

Whom Rasul Tutunov trusts overall

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

1. Richard S. Sutton
2. Ronald J. Williams
3. Jan Peters
4. Diederik P. Kingma
5. Alexander Olshevsky
6. Sergey Levine
7. Geoffrey E. Hinton
8. Yoshua Bengio
9. Haitham Bou-Ammar
10. John Schulman

Who trusts Rasul Tutunov overall

1. Joshua Achiam
2. Yu Zhang
3. A. Perera

Papers from Rasul Tutunov's perspective

Ordered by how strongly the researchers Rasul Tutunov 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Model-Based Stabilisation of Deep Reinforcement Learning (2018)
• Distributed Multitask Reinforcement Learning with Quadratic Convergence (2018) — 9 citations
• Safe Policy Search for Lifelong Reinforcement Learning with Sublinear Regret (2015) — 68 citations