J. Paul Brooks

Artificial Intelligence · 2011

A researcher in the Science corpus: 1 paper; trusts 25 researchers and is trusted by 21 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 10 citations into it; #5,445 of 35,345 by trust here, #20,377 by citations
• Statistical Learning Theory — 5 citations into it

Whom J. Paul Brooks trusts overall

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

1. Ingo Steinwart
2. Yuhai Wu
3. Peter L. Bartlett
4. Corinna Cortes
5. Bernhard Schölkopf
6. Ronan Collobert
7. Linli Xu
8. Vladimir Naumovich Vapnik
9. Shahar Mendelson
10. C. Burges

Who trusts J. Paul Brooks overall

1. Emilio Carrizosa
2. Cynthia Rudin
3. Berk Ustun
4. Dolores Romero Morales
5. Youngdong Kim
6. Amaya Nogales-Gómez
7. Pietro Belotti
8. Yining Wang
9. Belén Martín-Barragán
10. Junho Yim

Papers from J. Paul Brooks's perspective

Ordered by how strongly the researchers J. Paul Brooks 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
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. Going deeper with convolutions

Their papers

• Support Vector Machines with the Ramp Loss and the Hard Margin Loss (2011) — 154 citations