Mario Díaz

Artificial Intelligence · 2018–2019

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 — 42 citations into it
• Statistics and Probability — 14 citations into it
• Safety, Robustness & Interpretability — 12 citations into it
• Statistical Learning Theory — 10 citations into it
• Electrical and Electronic Engineering — 6 citations into it

Whom Mario Díaz trusts overall

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

1. Cynthia Dwork
2. Latanya Sweeney
3. Congzheng Song
4. Shai Shalev-Shwartz
5. Aolin Xu
6. Daniel Russo
7. Vitaly Shmatikov
8. Maxim Raginsky
9. Shai Ben-David
10. Lalitha Sankar

Papers from Mario Díaz's perspective

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

Their papers

• On the Robustness of Information-Theoretic Privacy Measures and Mechanisms (2018) — 58 citations
• Theoretical Guarantees for Model Auditing with Finite Adversaries (2019)