Jean Lafond

Artificial Intelligence · 2016–2017

A researcher in the Science corpus: 2 papers; trusts 24 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 18 citations into it
• Optimization & Training — 18 citations into it
• Computational Mechanics — 10 citations into it
• Computer Networks and Communications — 9 citations into it
• Computational Theory and Mathematics — 6 citations into it

Whom Jean Lafond trusts overall

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

1. Martin Jaggi
2. Francis R. Bach
3. Shun-ichi Amari
4. Alex Krizhevsky
5. N. Schraudolph
6. Yann Ollivier
7. Geoffrey E. Hinton
8. Sergey Ioffe
9. Jorge Nocedal
10. Lin Xiao

Who trusts Jean Lafond overall

1. Rachel A. Ward
2. Jinshan Zeng

Papers from Jean Lafond's perspective

Ordered by how strongly the researchers Jean Lafond 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. Learning Multiple Layers of Features from Tiny Images
9. Attention is All you Need (Neural Information Processing Systems)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Diagonal Rescaling For Neural Networks (2017) — 12 citations
• D-FW: Communication efficient distributed algorithms for high-dimensional sparse optimization (2016) — 13 citations