Manfred Huber

Reinforcement Learning · with Fakoor · 2003–2013

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 14 citations into it

Whom Manfred Huber trusts overall

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

1. Richard S. Sutton
2. Andrew Barto
3. Ronald E. Parr
4. Honglak Lee
5. Ben J. A. Kröse
6. Doina Precup

Who trusts Manfred Huber overall

1. Francisco M. Garcia
2. Tejas D. Kulkarni
3. Philip S. Thomas

Papers from Manfred Huber's perspective

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

1. Reinforcement Learning: An Introduction
2. ImageNet classification with deep convolutional neural networks
3. Gradient-based learning applied to document recognition
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Learning Multiple Layers of Features from Tiny Images
9. Reinforcement Learning: A Survey
10. Learning from delayed rewards

Their papers

• Using deep learning to enhance cancer diagnosis and classication (2013) — 258 citations
• Subgoal Discovery for Hierarchical Reinforcement Learning Using Learned Policies (2003) — 69 citations