Christopher D. Rosin

Artificial Intelligence · 1995–2011

A researcher in the Science corpus: 3 papers; trusts 25 researchers and is trusted by 36 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 11 citations into it; #7,426 of 35,345 by trust here, #23,731 by citations
• Reinforcement Learning — 10 citations into it; #674 of 2,242 by trust here, #1,844 by citations
• Management Science and Operations Research — 7 citations into it; #1,680 of 11,946 by trust here, #6,314 by citations

Whom Christopher D. Rosin trusts overall

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

1. Rémi Coulom
2. Sylvain Gelly
3. Peter Auer
4. J. Langford
5. David Silver
6. Jean-Yves Audibert
7. Levente Kocsis
8. Hilmar Finnsson
9. Nicolò Cesa-Bianchi
10. Sébastien Bubeck

Who trusts Christopher D. Rosin overall

1. Kenneth O. Stanley
2. Thomas Miconi
3. Risto Miikkulainen
4. Peter Stone
5. Zirui Zhao
6. Liviu Panait
7. David Silver
8. Kenneth A. De Jong
9. Shimon Whiteson
10. Jordan B. Pollack

Papers from Christopher D. Rosin's perspective

Ordered by how strongly the researchers Christopher D. Rosin 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. ImageNet classification with deep convolutional neural networks
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. ImageNet: A large-scale hierarchical image database
7. Learning Multiple Layers of Features from Tiny Images
8. Reinforcement Learning: An Introduction
9. Attention is All you Need (Neural Information Processing Systems)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Multi-armed bandits with episode context (2011) — 322 citations
• New Methods for Competitive Coevolution (1997)
• Methods for Competitive Co-Evolution: Finding Opponents Worth Beating (1995)