Simon Perkins

Artificial Intelligence · 2003

A researcher in the Science corpus: 3 papers; trusts 11 researchers and is trusted by 28 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 14 citations into it; #7,258 of 35,345 by trust here, #18,586 by citations
• Statistical Learning Theory — 6 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it; #11,309 of 21,575 by trust here, #16,367 by citations

Whom Simon Perkins trusts overall

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

1. Bernhard Schölkopf
2. Eric R. Ziegel
3. Alex Smola
4. Bernhard E. Boser
5. Robert Tibshirani
6. Federico Girosi
7. Vladimir Naumovich Vapnik
8. Jerome H. Friedman
9. Chih-Jen Lin
10. Tomaso A. Poggio

Who trusts Simon Perkins overall

1. Yangqing Jia
2. Stephen H. Bach
3. Isabelle M Guyon
4. Holger Hofling
5. Mark W. Schmidt
6. Jun Liu
7. Shay B. Cohen
8. Su-In Lee
9. Thomas Lavergne
10. Guo-Xun Yuan

Papers from Simon Perkins's perspective

Ordered by how strongly the researchers Simon Perkins 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

• Accurate On-line Support Vector Regression (2003) — 400 citations
• Time-series novelty detection using one-class support vector machines (2003) — 411 citations
• Grafting: Fast, Incremental Feature Selection by Gradient Descent in Function Space (2003) — 384 citations