Geoffrey Negiar

Optimization & Training · 2018

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Optimization & Training — 13 citations into it; #2,554 of 2,601 by trust here, #2,378 by citations
• Artificial Intelligence — 9 citations into it; #34,502 of 35,345 by trust here, #30,347 by citations
• Computational Mechanics — 8 citations into it; #9,687 of 10,001 by trust here, #8,258 by citations

Whom Geoffrey Negiar trusts overall

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

1. Simon Lacoste-Julien
2. Martin Jaggi
3. Yurii E. Nesterov
4. Stéphane Mallat
5. Amir Beck
6. Thomas Kerdreux
7. F. Maxwell Harper

Who trusts Geoffrey Negiar overall

1. Thomas Kerdreux
2. Xiangyu Yang
3. Ruichen Jiang

Papers from Geoffrey Negiar's perspective

Ordered by how strongly the researchers Geoffrey Negiar 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. Attention is All you Need (Neural Information Processing Systems)
5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
6. ImageNet: A large-scale hierarchical image database
7. An algorithm for quadratic programming
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Linearly Convergent Frank-Wolfe with Backtracking Line-Search. (2018) — 71 citations