Rahul Radhakrishnan Iyer

Reinforcement Learning · 2018

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 7 citations into it

Whom Rahul Radhakrishnan Iyer trusts overall

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

1. Richard S. Sutton
2. Ronald J. Williams
3. Volodymyr Mnih
4. Hado van Hasselt
5. Geoffrey E. Hinton
6. Alex Krizhevsky
7. Quoc V. Le
8. David Silver
9. Yoshua Bengio
10. Ziyun Wang

Who trusts Rahul Radhakrishnan Iyer overall

1. Raghuram Mandyam Annasamy
2. Akanksha Atrey
3. Zhibo Zhang
4. Xuhong Li
5. Katia P. Sycara
6. Kaleigh Clary

Papers from Rahul Radhakrishnan Iyer's perspective

Ordered by how strongly the researchers Rahul Radhakrishnan Iyer 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Going deeper with convolutions
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
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

• Transparency and Explanation in Deep Reinforcement Learning Neural Networks (2018) — 195 citations