Ruben Martinez-Cantin

Artificial Intelligence · 2007–2014

A researcher in the Science corpus: 4 papers; trusts 55 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 33 citations into it
• Reinforcement Learning — 18 citations into it
• Aerospace Engineering — 10 citations into it
• Computer Networks and Communications — 10 citations into it; #3,062 of 9,886 by trust here, #3,862 by citations
• Computational Theory and Mathematics — 9 citations into it
• Control and Systems Engineering — 9 citations into it; #4,673 of 8,257 by trust here, #5,490 by citations
• Management Science and Operations Research — 9 citations into it
• Mathematical Optimization — 8 citations into it

Whom Ruben Martinez-Cantin trusts overall

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

1. Donald R. Jones
2. Jan Peters
3. Katharina Eggensperger
4. Frank Hutter
5. M. Powell
6. Jan M. Maciejowski
7. Ziyun Wang
8. Carl E. Rasmussen
9. Ronald J. Williams
10. James Bergstra

Who trusts Ruben Martinez-Cantin overall

1. Duy Nguyen-Tuong
2. Li Yang
3. Kirthevasan Kandasamy
4. Ziyun Wang
5. Radwa El Shawi
6. Bobak Shahriari
7. Marc Claesen
8. Nando de Freitas
9. Julia Ling
10. Fernando Wario

Papers from Ruben Martinez-Cantin's perspective

Ordered by how strongly the researchers Ruben Martinez-Cantin 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
7. Learning Multiple Layers of Features from Tiny Images
8. Long Short-Term Memory
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• A Bayesian exploration-exploitation approach for optimal online sensing and planning with a visually guided mobile robot (2009) — 256 citations
• Body schema acquisition through active learning (2010) — 52 citations
• BayesOpt: a Bayesian optimization library for nonlinear optimization, experimental design and bandits (2014) — 317 citations
• Active Policy Learning for Robot Planning and Exploration under Uncertainty (2007) — 181 citations