David Roi Hardoon

Artificial Intelligence · 2004–2009

A researcher in the Science corpus: 4 papers; trusts 26 researchers and is trusted by 651 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 15 citations into it; #2,229 of 35,345 by trust here, #5,084 by citations
• Computer Vision and Pattern Recognition — 15 citations into it; #1,681 of 21,575 by trust here, #3,598 by citations
• Signal Processing — 6 citations into it; #218 of 7,572 by trust here, #462 by citations
• Statistical Learning Theory — 5 citations into it
• Representation & Self-Supervised Learning — 5 citations into it; #307 of 3,145 by trust here, #688 by citations

Whom David Roi Hardoon trusts overall

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

1. Robert Tibshirani
2. John Shawe-Taylor
3. Michael I. Jordan
4. Francis R. Bach
5. Shotaro Akaho
6. Krystian Mikolajczyk
7. David G. Lowe
8. Volker Roth
9. Nello Cristianini
10. Hui Zou

Who trusts David Roi Hardoon overall

1. Yuxin Peng
2. Tae-Kyun Kim
3. Micah Hodosh
4. Saeid Motiian
5. Liwei Wang
6. Yu Zheng
7. Shiliang Sun
8. Maithra Raghu
9. Jing Zhao
10. Xing Xu

Papers from David Roi Hardoon's perspective

Ordered by how strongly the researchers David Roi Hardoon 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. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Canonical Correlation Analysis: An Overview with Application to Learning Methods (2004) — 3,365 citations
• A Correlation Approach for Automatic Image Annotation (2006) — 53 citations
• Sparse canonical correlation analysis (2009) — 325 citations
• Two view learning: SVM-2K, Theory and Practice (2005) — 404 citations