Osher Lerner

Reinforcement Learning · 2018

A researcher in the Science corpus: 1 paper; trusts 47 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
• Optimization & Training — 7 citations into it

Whom Osher Lerner trusts overall

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

1. Longxin Lin
2. Shun-ichi Amari
3. James Martens
4. Diederik P. Kingma
5. Richard S. Sutton
6. Sham M. Kakade
7. Ben J. A. Kröse
8. G. Tesauro
9. Yoshua Bengio
10. Razvan Pascanu

Papers from Osher Lerner's perspective

Ordered by how strongly the researchers Osher Lerner trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Natural Gradient Deep Q-learning (2018) — 10 citations