Luiz F. O. Chamon

Artificial Intelligence · 2018–2021

A researcher in the Science corpus: 4 papers; trusts 32 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 107 citations into it; #26,789 of 35,345 by trust here, #25,040 by citations
• Safety, Robustness & Interpretability — 58 citations into it
• Computer Vision and Pattern Recognition — 37 citations into it
• Optimization & Training — 24 citations into it
• Reinforcement Learning — 18 citations into it
• Statistical Learning Theory — 14 citations into it
• Management Science and Operations Research — 12 citations into it
• Model Architectures — 12 citations into it

Whom Luiz F. O. Chamon trusts overall

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

1. Dimitri P. Bertsekas
2. Diederik P. Kingma
3. Eric R. Ziegel
4. Richard S. Sutton
5. Geoffrey E. Hinton
6. Ian J. Goodfellow
7. Radford M. Neal
8. Alex Krizhevsky
9. Jimmy Ba
10. Yoshua Bengio

Who trusts Luiz F. O. Chamon overall

1. Liangzu Peng
2. Paris V. Giampouras
3. René Vidal

Papers from Luiz F. O. Chamon's perspective

Ordered by how strongly the researchers Luiz F. O. Chamon 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. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
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

• Constrained Reinforcement Learning Has Zero Duality Gap (2019) — 258 citations
• Learning Optimal Resource Allocations in Wireless Systems (2018) — 237 citations
• Adversarial Robustness with Semi-Infinite Constrained Learning (2021) — 50 citations
• Constrained Learning With Non-Convex Losses (2021) — 65 citations