Javier García

Artificial Intelligence · with Fernández · 2007–2015

A researcher in the Science corpus: 3 papers; trusts 57 researchers and is trusted by 55 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 38 citations into it; #4,097 of 35,345 by trust here, #6,911 by citations
• Reinforcement Learning — 32 citations into it; #580 of 2,242 by trust here, #734 by citations
• Control and Systems Engineering — 11 citations into it; #822 of 8,257 by trust here, #618 by citations
• Computational Theory and Mathematics — 9 citations into it; #2,813 of 12,182 by trust here, #5,239 by citations
• Management Science and Operations Research — 5 citations into it

Whom Javier García trusts overall

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

1. Richard S. Sutton
2. Rogier Koppejan
3. Andrew Barto
4. Pieter Abbeel
5. William D. Smart
6. Matthias Heger
7. Leslie Pack Kaelbling
8. Fernando Fernández
9. Teodor Mihai Moldovan
10. Peter Stone

Who trusts Javier García overall

1. Matthew E. Taylor
2. Peter Stone
3. Stefan Depeweg
4. Edouard Leurent
5. Shivaram Kalyanakrishnan
6. Adith Swaminathan
7. Shangding Gu
8. Aravind Rajeswaran
9. Afshin Oroojlooyjadid
10. José Miguel Hernández-Lobato

Papers from Javier García's perspective

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

Their papers

• A comprehensive survey on safe reinforcement learning (2015) — 2,055 citations
• Safe Exploration of State and Action Spaces in Reinforcement Learning (2012) — 173 citations
• Reinforcement learning in the robocup-soccer keepaway (2007) — 396 citations