David Baldazo

Artificial Intelligence · 2017

A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 40 citations into it
• Reinforcement Learning — 32 citations into it
• Computer Networks and Communications — 12 citations into it
• Management Science and Operations Research — 9 citations into it
• Optimization & Training — 7 citations into it
• Electrical and Electronic Engineering — 6 citations into it

Whom David Baldazo trusts overall

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

1. Ronald J. Williams
2. Ali H. Sayed
3. Diederik P. Kingma
4. Jimmy Ba
5. Richard S. Sutton
6. Dimitri P. Bertsekas
7. Yoshua Bengio
8. Ermin Wei
9. Richard M. Karp
10. Geoffrey E. Hinton

Papers from David Baldazo's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
5. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
6. Asynchronous Methods for Deep Reinforcement Learning
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet: A large-scale hierarchical image database

Their papers

• Diff-DAC: Distributed Actor-Critic for Average Multitask Deep Reinforcement Learning (2017) — 31 citations
• Diff-DAC: Distributed Actor-Critic for Multitask Deep Reinforcement Learning (2017) — 17 citations