Ralph Neuneier

Reinforcement Learning · 1996–1998

A researcher in the Science corpus: 3 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 6 citations into it

Whom Ralph Neuneier trusts overall

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

1. Richard S. Sutton
2. Dimitri P. Bertsekas
3. Yann LeCun
4. Babak Hassibi
5. Geoffrey J. Gordon
6. John N. Tsitsiklis
7. John S. Denker

Who trusts Ralph Neuneier overall

1. N. Schraudolph
2. Daniel Hein
3. Laurence Aitchison
4. Steffen Udluft
5. Vasileios Belagiannis
6. Thomas A. Runkler
7. Alexander Hentschel
8. Christian Rupprecht
9. Trung Kien Vu
10. Davis W. Blalock

Papers from Ralph Neuneier's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Gradient-based learning applied to document recognition
3. ImageNet classification with deep convolutional neural networks
4. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
7. Stable Function Approximation in Dynamic Programming
8. Learning Multiple Layers of Features from Tiny Images
9. Learning to predict by the methods of temporal differences
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Risk-Sensitive Reinforcement Learning (1998)
• How to Train Neural Networks (1996)
• Early Brain Damage (1996)