Craig John Saunders

Artificial Intelligence · 1998–2006

A researcher in the Science corpus: 6 papers; trusts 20 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 18 citations into it
• Statistical Learning Theory — 10 citations into it
• Computer Vision and Pattern Recognition — 9 citations into it
• Scaling & Learning Theory — 7 citations into it
• Probabilistic & Bayesian Methods — 5 citations into it

Whom Craig John Saunders trusts overall

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

1. Vladimir Naumovich Vapni
2. Yuhai Wu
3. Vladimir Naumovich Vapnik
4. A. Gammerman
5. Grace Wahba
6. Vladimir G Vovk
7. Thorsten Joachims
8. Krystian Mikolajczyk
9. David G. Lowe
10. Dustin Boswell

Who trusts Craig John Saunders overall

1. Corinna Cortes
2. Johan A. K. Suykens
3. Mehryar Mohri
4. Vladimir G Vovk
5. Roman Rosipal
6. Martin Jaggi
7. Tony Van Gestel
8. Afshin Rostamizadeh
9. Anastasios Nikolas Angelopoulos
10. Nicolas Papernot

Papers from Craig John Saunders's perspective

Ordered by how strongly the researchers Craig John Saunders 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. 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

• A Correlation Approach for Automatic Image Annotation (2006) — 53 citations
• Kernel-Based Learning of Hierarchical Multilabel Classification Models (2006) — 306 citations
• Text Classification using String Kernels (2002) — 1,476 citations
• Machine-Learning Applications of Algorithmic Randomness (1999)
• Transduction with Confidence and Credibility (1999)
• Ridge Regression Learning Algorithm in Dual Variables (1998)